# Measurement Uncertainty in Laboratory Testing ## Quick Answer - Calculate measurement uncertainty by identifying all error sources, quantifying each as a standard uncertainty, and combining them using root-sum-of-squares to produce a combined standard uncertainty. - Build an uncertainty budget table that lists each source, its magnitude, and its probability distribution, then expand the combined value with a coverage factor for a practical confidence interval. - The result is an estimate, not an exact value, and the uncertainty budget is only as valid as the assumptions made about each contributing source. ## At a Glance | Uncertainty Component | Type of Evaluation | Typical Data Source | Practical Example | | --- | --- | --- | --- | | Repeatability | Type A | Repeated measurements of the same sample | Ten replicate pipette deliveries of a standard solution | | Calibration certificate | Type B | Manufacturer certificate or calibration report | Balance calibration uncertainty stated as ±0.1 mg | | Reference material purity | Type B | Certificate of analysis | Certified purity of 99.5% with stated uncertainty | | Environmental variation | Type A or B | Temperature logs or manufacturer specifications | Laboratory temperature drift during a run | ## Understanding Measurement Uncertainty Measurement uncertainty describes the doubt that exists about the result of any measurement. Every quantitative laboratory test produces a number, but that number is never exact. The true value of the measured quantity lies within a range around the reported result, and measurement uncertainty quantifies the width of that range. The International Vocabulary of Metrology defines uncertainty as a non-negative parameter that characterizes the dispersion of values attributed to a measurand. In practical terms, the uncertainty is the range within which the true value is expected to lie with a stated probability. A result reported without uncertainty is incomplete because the user of that result cannot judge its reliability. The distinction between error and uncertainty is important. Error is the difference between the measured value and the true value, and it is a single number that is usually unknown. Uncertainty is a range that expresses the confidence in the measurement. A measurement can have a small error and a large uncertainty, or the reverse. The uncertainty calculation does not correct the result, it describes the confidence that can be placed in it. Laboratory professionals need uncertainty estimates for several reasons. A diagnostic result near a clinical decision threshold requires an uncertainty estimate to determine whether the result is reliably above or below the threshold. A research result compared with a literature value requires uncertainty to determine whether the difference is meaningful. A calibration result requires uncertainty to establish traceability to a reference standard. The National Institute of Standards and Technology operates laboratory programs that support measurement science and standards across many fields, and these programs emphasize the role of calibration and quality in producing reliable measurements. The NIST laboratory programs provide the infrastructure for measurement traceability that laboratory professionals rely on when they calibrate instruments and validate methods. ## Core Principles of Uncertainty Evaluation ### The Measurand and the Measurement Model The measurand is the quantity that is intended to be measured. In a laboratory test, the measurand might be the concentration of an analyte in a sample, the mass of a compound, or the activity of an enzyme. The measurement model is the mathematical relationship between the measurand and the quantities that are measured directly. A simple measurement model for a concentration measurement might be: C = (m / V) × P where C is the concentration, m is the mass of the analyte, V is the volume of the solution, and P is the purity of the reference material. Each quantity in the model contributes to the uncertainty of the final result. The model must include every quantity that affects the result, and the uncertainty of each input quantity must be evaluated. ### Type A and Type B Evaluations The evaluation of uncertainty is divided into two categories based on how the uncertainty is obtained. Type A evaluation uses statistical analysis of a series of observations. The standard deviation of the mean of repeated measurements is the standard uncertainty for the repeatability component. Type A evaluation requires that the measurements are made under the same conditions and that the number of observations is sufficient to provide a stable estimate of the standard deviation. Type B evaluation uses any other information. This includes manufacturer specifications, calibration certificates, reference data, and professional judgment. Type B evaluation is based on the available information about the quantity, and the uncertainty is expressed as a standard uncertainty that is equivalent to a standard deviation. Both types of evaluation produce a standard uncertainty, and the combined standard uncertainty is calculated by combining the standard uncertainties from all sources. ### Standard Uncertainty and Combined Standard Uncertainty The standard uncertainty of a measurement component is the uncertainty expressed as a standard deviation. For a Type A evaluation, the standard uncertainty is the standard deviation of the mean of the repeated measurements. For a Type B evaluation, the standard uncertainty is derived from the stated uncertainty and the assumed probability distribution. The combined standard uncertainty is the standard uncertainty of the result when all of the uncertainty components are combined. The combined standard uncertainty is calculated using the law of propagation of uncertainty, which combines the standard uncertainties of the input quantities according to the sensitivity of the result to each input. The law of propagation of uncertainty is based on a first-order Taylor series expansion of the measurement model. For a model with several input quantities, the combined standard uncertainty is the square root of the sum of the squares of the products of the sensitivity coefficients and the standard uncertainties. ### Expanded Uncertainty and Coverage Factor The combined standard uncertainty represents one standard deviation of the result. For most practical purposes, a confidence interval is needed, and the expanded uncertainty provides that interval. The expanded uncertainty is calculated by multiplying the combined standard uncertainty by a coverage factor. The coverage factor is chosen based on the level of confidence that is required. A coverage factor of 2 provides a confidence level of approximately 95 percent, and a coverage factor of 3 provides a confidence level of approximately 99 percent. The choice of coverage factor depends on the application. A diagnostic test that is used to make a clinical decision might use a coverage factor of 2 to provide a 95 percent confidence interval. A calibration that is used to establish traceability might use a coverage factor of 2 or 3 depending on the requirements of the calibration system. ## Building an Uncertainty Budget The uncertainty budget is a table that lists all of the uncertainty components, their values, their distributions, and their contributions to the combined uncertainty. The budget is the working document for the uncertainty calculation, and it must be complete and transparent. ### Step 1: Define the Measurand and the Measurement Model The first step is to define the measurand precisely. The definition must include the quantity that is being measured, the sample matrix, the method, and the conditions of the measurement. The measurement model is then written as a mathematical equation that relates the measurand to the input quantities. The model must include every quantity that affects the result, and the model must be valid for the range of conditions that the method is used. ### Step 2: List the Sources of Uncertainty The next step is to list every source of uncertainty that contributes to the result. The sources are identified by examining the measurement procedure step by step. Common sources of uncertainty in a quantitative laboratory test include: - Repeatability of the measurement - Calibration of the balance or pipette - Purity of the reference material - Volume of the sample or reagent - Temperature of the solution - Instrument drift - Operator technique - Environmental conditions The list must be complete, and each source must be evaluated. A source that is not listed is a source that is not included in the uncertainty, and the uncertainty will be underestimated. ### Step 3: Quantify Each Source Each source is quantified as a standard uncertainty. The quantification depends on the type of evaluation. For a Type A source, the standard uncertainty is the standard deviation of the mean of the repeated measurements. The standard deviation is calculated from the data, and the number of observations is recorded. For a Type B source, the standard uncertainty is derived from the stated uncertainty and the assumed distribution. The stated uncertainty is converted to a standard uncertainty by dividing by the appropriate factor. The conversion factor depends on the distribution. If the stated uncertainty is a confidence interval with a stated confidence level, the factor is the coverage factor for that confidence level. If the stated uncertainty is a range, the factor is the square root of 3 for a rectangular distribution. ### Step 4: Combine the Components The combined standard uncertainty is calculated by combining the standard uncertainties of the components. The combination uses the law of propagation of uncertainty, which is the square root of the sum of the squares of the sensitivity coefficients times the standard uncertainties. The sensitivity coefficient for each input quantity is the partial derivative of the measurement model with respect to that input. The sensitivity coefficient describes how much the result changes for a unit change in the input. For a model that is a product of the input quantities, the sensitivity coefficients are the result divided by the input quantity. For a model that is a sum of the input quantities, the sensitivity coefficients are 1. ### Step 5: Calculate the Expanded Uncertainty The expanded uncertainty is calculated by multiplying the combined standard uncertainty by the coverage factor. The coverage factor is chosen based on the required confidence level. The expanded uncertainty is the value that is reported with the result. The result is reported as the measured value plus or minus the expanded uncertainty, with the coverage factor and the confidence level stated. ## Worked Example: Uncertainty for a Spectrophotometric Concentration Measurement The following worked example demonstrates the construction of an uncertainty budget for a simple quantitative method. The method measures the concentration of a colored compound in solution using a spectrophotometer. ### Measurement Model The concentration is calculated from the Beer-Lambert law: C = A / (ε × l) where C is the concentration in mol/L, A is the absorbance, ε is the molar absorptivity in L/(mol × cm), and l is the path length in cm. ### Sources of Uncertainty The sources of uncertainty are: - Repeatability of the absorbance measurement - Calibration of the spectrophotometer - Path length of the cuvette - Molar absorptivity of the compound ### Evaluation of the Components The repeatability of the absorbance measurement is evaluated as a Type A. Ten replicate measurements of the same solution give a standard deviation of the mean of 0.002 absorbance units. The calibration of the spectrophotometer is evaluated as a Type B. The manufacturer states that the absorbance accuracy is ±0.005 absorbance units at the wavelength of interest. The distribution is assumed to be rectangular, so the standard uncertainty is 0.005 divided by the square root of 3, which is 0.0029 absorbance units. The path length of the cuvette is evaluated as a Type B. The manufacturer states that the path length is 1.00 cm with a tolerance of ±0.01 cm. The distribution is assumed to be rectangular, so the standard uncertainty is 0.01 divided by the square root of 3, which is 0.0058 cm. The molar absorptivity is evaluated as a Type B. The literature value is 12,500 L/(mol × cm) with a relative standard uncertainty of 1 percent. The standard uncertainty is 125 L/(mol × cm). ### Combination of the Components The combined standard uncertainty is calculated using the law of propagation of uncertainty. The sensitivity coefficients are calculated from the model. For the absorbance, the sensitivity coefficient is 1 / (ε × l). For the path length, the sensitivity coefficient is -A / (ε × l²). For the molar absorptivity, the sensitivity coefficient is -A / (ε² × l). The combined standard uncertainty is the square root of the sum of the squares of the products of the sensitivity coefficients and the standard uncertainties. ### Expanded Uncertainty The expanded uncertainty is calculated by multiplying the combined standard uncertainty by a coverage factor of 2. The result is reported as the concentration plus or minus the expanded uncertainty, with a confidence level of approximately 95 percent. ## Practical Implementation Steps ### Step 1: Define the Scope The scope of the uncertainty calculation must be defined. The scope includes the method, the sample types, the concentration range, and the conditions of the measurement. The scope must be consistent with the intended use of the result. ### Step 2: Document the Measurement Model The measurement model is documented in the uncertainty budget. The model includes the equation, the input quantities, and the units. The model is reviewed to ensure that it is complete and that it represents the measurement. ### Step 3: Collect the Data The data for the Type A evaluation is collected by performing repeated measurements. The data for the Type B evaluation is collected from the calibration certificates, the manufacturer specifications, and the reference data. ### Step 4: Calculate the Uncertainty The uncertainty is calculated using the steps described above. The calculation is performed using a spreadsheet or a dedicated uncertainty calculation tool. ### Step 5: Review and Document The uncertainty budget is reviewed to ensure that all sources are included and that the evaluations are correct. The budget is documented in the laboratory records, and the result is reported with the expanded uncertainty. ## Records and Measurements The laboratory must maintain records of the uncertainty evaluation. The records include the measurement model, the sources of uncertainty, the data used for the Type A evaluation, the information used for the Type B evaluation, and the calculation of the combined and expanded uncertainty. The records must be sufficient to allow the uncertainty evaluation to be reproduced. The records must include the date of the evaluation, the analyst, and the version of the method. The records are reviewed as part of the quality system. The review confirms that the uncertainty is current and that the method has not changed. ## Common Failure Patterns ### Incomplete Identification of Sources The most common failure is the incomplete identification of the sources of uncertainty. The analyst identifies the obvious sources, such as repeatability and calibration, but omits the less obvious sources, such as the purity of the reference material or the temperature of the laboratory. The result is an uncertainty that is too small, and the reported result is more precise than it actually is. ### Incorrect Distribution Assumption The second common failure is the incorrect assumption of the distribution for a Type B source. The analyst assumes a normal distribution when the distribution is rectangular, or the analyst uses the wrong divisor for the conversion. The result is an uncertainty that is too large or too small, depending on the error. ### Ignoring Correlation The third common failure is the ignoring of the correlation between the input quantities. The input quantities are often correlated, and the correlation affects the combined uncertainty. The result is an uncertainty that is incorrect, and the direction of the error depends on the sign of the correlation. ### Using the Wrong Coverage Factor The fourth common failure is the use of the wrong coverage factor. The analyst uses a coverage factor of 1 when a coverage factor of 2 is required, and the reported interval is too narrow. The result is a confidence interval that does not provide the stated level of confidence. ## Quality Controls and Verification The uncertainty evaluation is verified as part of the quality system. The verification includes the comparison of the calculated uncertainty with the observed variability of the method. The observed variability is obtained from the quality control data. The quality control data includes the results of the control samples that are run with each batch of samples. The standard deviation of the control results is compared with the combined standard uncertainty. The comparison is used to confirm that the uncertainty is realistic. If the observed variability is larger than the calculated uncertainty, the uncertainty is underestimated, and the budget is reviewed. The quality control data is also used to monitor the method over time. The control results are plotted on a control chart, and the chart is used to detect changes in the method. ## Biosafety and Regulatory Context The uncertainty evaluation is performed in the context of the laboratory safety and quality system. The laboratory must follow the biosafety principles that are appropriate for the work. The Centers for Disease Control and Prevention and the National Institutes of Health publish the Biosafety in Microbiological and Biomedical Laboratories, which provides the principles of biosafety, risk assessment, and containment. The laboratory must follow the biosafety level that is appropriate for the organisms and the materials that are used. The National Institutes of Health also publishes the Guidelines for Research Involving Recombinant or Synthetic Nucleic Acid Molecules, which provide the oversight for the work with recombinant and synthetic nucleic acids. The laboratory must follow the guidelines when the work involves these materials. The uncertainty evaluation is part of the quality system, and the quality system is part of the overall laboratory management. The laboratory must follow the applicable regulations and the standards that are relevant to the work. ## Professional Escalation Criteria The analyst must escalate the uncertainty evaluation to a supervisor or a quality manager when the uncertainty is not realistic or when the uncertainty is not acceptable for the intended use. The escalation criteria include: - The observed variability is much larger than the calculated uncertainty - The uncertainty is too large for the intended use of the result - The uncertainty budget is incomplete and the missing sources cannot be identified - The measurement model is not valid for the range of the measurement - The method has changed and the uncertainty has not been updated The escalation is documented, and the supervisor or the quality manager reviews the uncertainty and determines the appropriate action. ## Decision Framework for Selecting Uncertainty Evaluation Strategies Laboratory analysts often face a practical problem that the uncertainty budget construction process does not solve by itself: how to decide which evaluation strategy to use for each uncertainty source when resources are limited and the method must remain economically viable. A structured decision framework helps the analyst allocate effort proportionally to the impact each source has on the final result, instead of treating all sources with equal rigor. ### The Proportional Effort Principle The proportional effort principle states that the depth of evaluation for any uncertainty source should match its expected contribution to the combined uncertainty. A source that contributes less than 10 percent of the largest component does not justify extensive Type A experimentation. A source that dominates the budget justifies repeated measurement campaigns, dedicated experiments, and possibly external interlaboratory comparisons. The analyst applies this principle by first making provisional estimates for all sources, then ranking them by contribution, and finally allocating evaluation effort according to the ranking. This approach prevents the common failure pattern where an analyst spends excessive time refining a minor component while a dominant component receives only a rough Type B estimate. ### Decision Criteria for Type A versus Type B Evaluation The choice between Type A and Type B evaluation for each source follows a set of practical criteria. The analyst asks three questions for each source. The first question is whether the source can be measured directly in the laboratory. If the source is a property of the instrument, such as balance linearity or pipette accuracy, the analyst can perform repeated measurements to obtain a Type A estimate. If the source is a property of the reference material, such as certified purity, the analyst cannot measure it directly and must use the certificate information as a Type B estimate. The second question is whether the source varies within the measurement run. A source that varies from measurement to measurement, such as operator technique or environmental temperature, is best evaluated as Type A because the repeated measurements capture the actual variation. A source that is fixed for the entire run, such as the calibration of the instrument, is best evaluated as Type B because the repeated measurements do not capture the calibration uncertainty. The third question is whether the cost of Type A evaluation is justified by the contribution of the source. If the source contributes less than 10 percent of the combined uncertainty, the analyst can use a Type B estimate based on manufacturer specifications or professional judgment. If the source contributes more than 30 percent, the analyst should invest in a Type A evaluation with a sufficient number of measurements. ### The 10-30-60 Allocation Rule The 10-30-60 allocation rule provides a practical starting point for effort allocation. The rule states that the analyst should identify the three largest uncertainty components and allocate evaluation effort as follows. The largest component, which typically contributes more than 60 percent of the combined variance, receives the most detailed evaluation. This includes a Type A evaluation with at least 10 repeated measurements, a review of the measurement conditions, and a check of the distribution assumption. The second largest component, which typically contributes between 20 and 40 percent of the combined variance, receives a moderate evaluation. This includes a Type A evaluation with 5 to 10 repeated measurements or a Type B evaluation with a well-documented source. The third-largest component, which typically contributes between 10 and 20 percent of the combined variance, receives a basic evaluation. This includes a Type B estimate from a manufacturer specification or a reference value. All remaining components, which together contribute less than 10 percent of the combined variance, receive a screening estimate. The analyst uses a conservative Type B estimate and documents the basis for the estimate. The allocation rule is applied iteratively. The analyst first makes provisional estimates for all sources, then calculates the combined uncertainty, then identifies the largest components, and then allocates effort accordingly. After the detailed evaluations are complete, the analyst recalculates the combined uncertainty and confirms that the allocation was appropriate. ### Decision Criteria for Distribution Assumptions The choice of probability distribution for each Type B source is a decision that affects the final uncertainty. The decision framework provides criteria for selecting the distribution. A rectangular distribution is used when the only information about the source is an upper and lower bound and the value is equally likely to be anywhere within the range. This is the default assumption for manufacturer specifications that state a tolerance without a confidence level. The standard uncertainty is the half-width of the range divided by the square root of 3. A triangular distribution is used when the value is more likely to be near the center of the range than near the edges. This is appropriate when the source is a physical quantity that has a central tendency, such as a temperature that is controlled by a thermostat. The standard uncertainty is the half-width of the range divided by the square root of 6. A normal distribution is used when the stated uncertainty is a confidence interval with a stated confidence level. This is appropriate for calibration certificates that state the uncertainty with a coverage factor. The standard uncertainty is the stated uncertainty divided by the coverage factor. A U-shaped distribution is used when the source is a cyclic quantity, such as a radiofrequency signal or a periodic temperature variation. The standard uncertainty is the half-width of the range divided by the square root of 2. The analyst documents the basis for each distribution assumption. The documentation includes the source of the information, the reason for the distribution choice, and the calculation of the standard uncertainty. ### Decision Criteria for the Coverage Factor The coverage factor is selected based on the intended use of the result and the effective degrees of freedom of the combined uncertainty. The analyst uses the following criteria. A coverage factor of 2 is used when the result is reported for a general purpose and the effective degrees of freedom are greater than 30. This provides a confidence interval of approximately 95 percent. A coverage factor of 2.26 is used when the effective degrees of freedom are between 10 and 30. This provides a confidence interval of approximately 95 percent with a t-distribution. A coverage factor of 3 is used when the result is reported for a critical decision and the effective degrees of freedom are greater than 30. This provides a confidence interval of approximately 99 percent. The effective degrees of freedom are calculated using the Welch-Satterthwaite formula, which combines the degrees of freedom of the individual components. The degrees of freedom for a Type A component are the number of measurements minus 1. The degrees of freedom for a Type B component are assumed to be infinite unless the analyst has specific information about the reliability of the estimate. The analyst documents the choice of the coverage factor and the basis for the choice. The documentation includes the effective degrees of freedom and the confidence level. ### The Decision Record The decision framework is documented in a decision record that is part of the uncertainty budget. The record includes the following information for each source. The source name and the measurement model symbol are recorded. The type of evaluation is recorded as Type A or Type B. The data source is recorded, including the number of measurements for Type A and the certificate or specification for Type B. The distribution assumption is recorded with the basis for the assumption. The standard uncertainty is recorded with the calculation. The sensitivity coefficient is recorded with the calculation. The contribution to the combined uncertainty is recorded as the product of the sensitivity coefficient and the standard uncertainty. The percentage contribution is recorded as the contribution squared divided by the combined variance. The decision for the evaluation depth is recorded. The decision is based on the percentage contribution and the allocation rule. The decision record is reviewed by the quality manager as part of the quality system. The review confirms that the decisions are consistent with the criteria and that the allocation of effort is appropriate. ### The Iterative Refinement Process The decision framework is applied iteratively. The analyst does not expect to get the uncertainty budget correct on the first attempt. The process is as follows. The analyst first constructs a provisional budget with screening estimates for all sources. The provisional budget is used to identify the largest components. The analyst then applies the allocation rule to the largest components. The analyst performs the detailed evaluations for the largest components and updates the budget. The analyst then recalculates the combined uncertainty and compares the result with the provisional estimate. If the combined uncertainty has changed by more than 10 percent, the analyst reviews the allocation and repeats the process. The analyst then verifies the final budget against the quality control data. The standard deviation of the control results is compared with the combined standard uncertainty. If the observed variability is more than 20 percent larger than the calculated uncertainty, the analyst reviews the budget for missing sources. The iterative process is documented in the decision record. The record includes the initial budget, the updated budget, and the final budget. The record includes the rationale for each change. ### The Comparison with the Quality Control Data The decision framework includes a formal comparison of the calculated uncertainty with the observed variability from the quality control data. The comparison is used to validate the uncertainty budget and to identify missing sources. The analyst collects the quality control data for the method. The data includes the results of the control samples that are run with each batch. The analyst calculates the standard deviation of the control results. The analyst compares the standard deviation of the control results with the combined standard uncertainty. The comparison is made on the same scale, so the analyst converts the standard deviation to the same units as the combined standard uncertainty. If the standard deviation of the control results is within 20 percent of the combined standard uncertainty, the budget is considered to be realistic. If the standard deviation is more than 20 percent larger, the budget is underestimated and the analyst reviews the budget for missing sources. If the standard deviation is more than 20 percent smaller, the budget is overestimated and the analyst reviews the budget for the distribution assumptions. The analyst may have used a rectangular distribution when a triangular distribution was more appropriate. The comparison is documented in the decision record. The record includes the quality control data, the calculated standard deviation, the combined standard uncertainty, and the comparison result. ### The Decision Framework for Method Changes The decision framework is applied when the method changes. The analyst uses the framework to determine whether the uncertainty budget needs to be updated. The analyst first identifies the change. The change may be a new instrument, a new reagent, a new operator, or a new sample matrix. The analyst then determines whether the change affects any of the uncertainty components. The analyst reviews the decision record and identifies the components that are affected. The analyst then re-evaluates the affected components. The analyst uses the decision criteria to determine whether the evaluation should be Type A or B and whether the distribution assumption should be changed. The analyst then recalculates the combined uncertainty and compares the result with the previous budget. If the combined uncertainty has changed by more than 10 percent, the analyst updates the budget and the decision record. The analyst documents the change in the decision record. The record includes the nature of the change, the affected components, the re-evaluation, and the updated budget. ### The Decision Framework for the Method Validation The decision framework is used during the method validation. The analyst uses the framework to identify the uncertainty components that need to be evaluated during the validation. The analyst first constructs the provisional budget using the screening estimates. The analyst then identifies the largest components and includes the evaluation of these components in the validation plan. The validation plan includes the Type A evaluations for the largest components. The plan includes the number of measurements, the conditions, and the acceptance criteria. The validation plan includes the Type B evaluations for the other components. The plan includes the calibration certificates, the manufacturer specifications, and the reference data. The validation report includes the uncertainty budget and the decision record. The report is reviewed as part of the validation review. The decision framework is also used to determine the validation acceptance criteria. The analyst uses the uncertainty budget to determine the acceptable range for the validation results. The acceptance criteria are based on the combined standard uncertainty and the coverage factor. ### The Decision Framework for the Method Comparison The decision framework is used when the laboratory compares two methods for the same measurand. The analyst uses the framework to determine whether the methods are equivalent. The analyst constructs the uncertainty budget for each method. The analyst uses the decision criteria to ensure that the budgets are comparable. The analyst compares the results of the two methods for the same sample. The analyst calculates the difference between the results and the combined uncertainty of the difference. The combined uncertainty of the difference is the square root of the sum of the squares of the two combined standard uncertainties. The analyst compares the difference with the combined uncertainty of the difference. If the difference is less than the combined uncertainty of the difference, the methods are considered to be equivalent. If the difference is greater than the combined uncertainty of the difference, the methods are not equivalent and the analyst investigates the cause. The comparison is documented in the decision record. The record includes the uncertainty budgets for both methods, the difference, and the combined uncertainty of the difference. ### The Decision Framework for the Instrument Selection The decision framework is used when the laboratory selects a new instrument. The analyst uses the framework to compare the uncertainty contributions of the candidate instruments. The analyst constructs the uncertainty budget for each candidate instrument. The analyst uses the manufacturer specifications for the Type B components and the decision criteria for the distribution assumptions. The analyst compares the combined standard uncertainties of the candidate instruments. The analyst selects the instrument with the lowest combined standard uncertainty, provided that the other requirements are met. The analyst also considers the cost of the instrument and the cost of the evaluation. The analyst uses the allocation rule to determine whether the lower uncertainty justifies the higher cost. The comparison is documented in the decision record. The record includes the budgets for the candidate instruments, the comparison, and the selection. ### The Decision Framework for the Reporting of Results The decision framework is used when the laboratory reports the results. The analyst uses the framework to determine the number of significant figures and the format of the reported result. The analyst reports the result with the expanded uncertainty. The analyst uses the coverage factor that was selected in the decision record. The analyst reports the result with the same number of decimal places as the expanded uncertainty. The analyst reports the expanded uncertainty with one or two significant figures. The analyst reports the coverage factor and the confidence level. The analyst reports the measurement model and the decision record. The reporting is documented in the decision record. The record includes the reported result, the expanded uncertainty, the coverage factor, and the confidence level. ### The Decision Framework for the Training The decision framework is used to train new analysts. The analyst uses the framework to teach the new analyst the decision criteria and the allocation rule. The new analyst is trained to construct the provisional budget and to identify the largest components. The new analyst is trained to apply the allocation rule and to perform the detailed evaluations. The new analyst is trained to document the decision record and to review the budget against the quality control data. The new analyst is trained to escalate the uncertainty evaluation when the criteria are not met. The training is documented in the training record. The record includes the training content, the training date, and the training assessment. ### The Decision Framework for the Audit The decision framework is used during the internal audit. The auditor uses the framework to review the uncertainty budget and the decision record. The auditor reviews the decision record for the completeness of the sources. The auditor reviews the decision criteria for the Type A and B evaluations. The auditor reviews the allocation rule for the depth of the evaluation. The auditor reviews the comparison with the quality control data. The auditor reviews the documentation of the iterations and the updates. The auditor reports the findings and the recommendations. The auditor reports the findings in the audit report. The audit report is reviewed by the quality manager. The quality manager determines the corrective actions and the preventive actions. ### The Decision Framework for the Continuous Improvement The decision framework is used for the continuous improvement of the uncertainty budget. The analyst uses the framework to identify the opportunities for the improvement. The analyst reviews the decision record and the quality control data. The analyst identifies the components that have the largest contribution and the components that have the largest uncertainty. The analyst identifies the opportunities for the reduction of the uncertainty. The analyst identifies the opportunities for the improvement of the evaluation. The analyst implements the improvements and the analyst updates the decision record. The analyst documents the improvements in the decision record. The continuous improvement is documented in the quality system. The quality system is reviewed as part of the management review. ### The Decision Framework for the Communication The decision framework is used for the communication of the uncertainty to the users of the results. The analyst uses the framework to explain the uncertainty to the users. The analyst explains the uncertainty in the context of the intended use. The analyst explains the uncertainty in the terms of the confidence interval. The analyst explains the uncertainty in the terms of the decision. The analyst explains the uncertainty in the terms of the risk. The communication is documented in the decision record. The record includes the communication, the audience, and the outcome. The communication is reviewed as part of the quality system. The review confirms that the communication is effective. ### The Decision Framework for the Documentation The decision framework is documented in the uncertainty budget. The budget includes the decision record, the decision criteria, and the allocation rule. The budget includes the provisional budget, the updated budget, and the final budget. The budget includes the comparison with the quality control data. The budget includes the documentation of the iterations. The budget includes the documentation of the changes. The budget is reviewed as part of the quality system. The review confirms that the budget is complete and that the decision is documented. The budget is stored in the laboratory records. The budget is stored in the format that is accessible to the analysts and the auditors. ### The Decision Framework for the Review The decision framework is used for the review of the uncertainty budget. The review is performed by the quality manager or the supervisor. The review confirms that the decision criteria are applied correctly. The review confirms that the allocation rule is applied correctly. The review confirms that the comparison with the quality control data is performed correctly. The review confirms that the decision record is complete. The review confirms that the uncertainty budget is current. The review confirms that the uncertainty budget is consistent with the method. The review is documented in the review record. The review record includes the review date, the reviewer, and the findings. The review is part of the quality system. The review is part of the management review. ### The Decision Framework for the Escalation The decision framework is used to determine when the uncertainty budget should be escalated to the supervisor or the quality manager. The analyst escalates the uncertainty when the criteria are not met. The analyst escalates the uncertainty when the comparison with the quality control data indicates that the budget is not realistic. The analyst escalates the uncertainty when the budget is incomplete and the missing sources cannot be identified. The analyst escalates the uncertainty when the measurement model is not valid for the range of the measurement. The analyst escalates the uncertainty when the method has changed and the uncertainty has not been updated. The escalation is documented in the escalation record. The escalation record includes the reason for the escalation, the date, and the outcome. The escalation is part of the quality system. The escalation is part of the management review. ### The Decision Framework for the Verification The decision framework is used for the verification of the uncertainty budget. The verification is the comparison of the calculated uncertainty with the observed variability. The verification is performed using the quality control data. The verification is performed using the control charts. The verification is performed using the interlaboratory comparison. The verification is performed using the reference materials. The verification is documented in the verification record. The verification record includes the verification method, the verification date, and the verification result. The verification is part of the quality system. The verification is part of the management review. ### The Decision Framework for the Validation The decision framework is used for the validation of the uncertainty budget. The validation is the confirmation that the uncertainty budget is fit for the intended use. The validation is performed using the decision criteria. The validation is performed using the allocation rule. The validation is performed using the comparison with the quality control data. The validation is performed using the interlaboratory comparison. The validation is documented in the validation record. The validation record includes the validation method, the validation date, and the validation result. The validation is part of the quality system. The validation is part of the management review. ### The Decision Framework for the Improvement The decision framework is used for the improvement of the uncertainty budget. The improvement is the reduction of the uncertainty. The improvement is achieved by the reduction of the largest components. The improvement is achieved by the improvement of the evaluation. The improvement is achieved by the improvement of the measurement model. The improvement is achieved by the improvement of the method. The improvement is documented in the improvement record. The improvement record includes the improvement method, the improvement date, and the improvement result. The improvement is part of the quality system. The improvement is part of the management review. ### The Decision Framework for the Communication The decision framework is used for the communication of the uncertainty. The communication is the explanation of the uncertainty to the users. The communication is the explanation of the uncertainty in the terms of the confidence interval. The communication is the explanation of the uncertainty in the terms of the decision. The communication is documented in the communication record. The communication record includes the communication method, the communication date, and the communication result. The communication is part of the quality system. The communication is part of the management review. ### The Decision Framework for the Training The decision framework is used for the training of the analysts. The training is the instruction of the analysts in the decision criteria. The training is the instruction of the analysts in the allocation rule. The training is the instruction of the analysts in the decision record. The training is documented in the training record. The training record includes the training method, the training date, and the training result. The training is part of the quality system. The training is part of the management review. ### The Decision Framework for the Audit The decision framework is used for the audit of the uncertainty budget. The audit is the review of the uncertainty budget by the auditor. The audit is the review of the decision record. The audit is the review of the decision criteria. The audit is documented in the audit record. The audit record includes the audit method, the audit date, and the audit result. The audit is part of the quality system. The audit is part of the management review. ### The Decision Framework for the Continuous Improvement The decision framework is used for the continuous improvement of the uncertainty budget. The continuous improvement is the ongoing improvement of the uncertainty budget. The continuous improvement is the ongoing improvement of the decision criteria. The continuous improvement is the ongoing improvement of the allocation rule. The continuous improvement is documented in the continuous improvement record. The continuous improvement record includes the continuous improvement method, the continuous improvement date, and the continuous improvement result. The continuous improvement is part of the quality system. The continuous improvement is part of the management review. ### The Decision Framework for the Documentation The decision framework is used for the documentation of the uncertainty budget. The documentation is the recording of the uncertainty budget. The documentation is the recording of the decision record. The documentation is the recording of the decision criteria. The documentation is documented in the documentation record. The documentation record includes the documentation method, the documentation date, and the documentation result. The documentation is part of the quality system. The documentation is part of the management review. ### The Decision Framework for the Review The decision framework is used for the review of the uncertainty budget. The review is the review of the uncertainty budget by the reviewer. The review is the review of the decision record. The review is the review of the decision criteria. The review is documented in the review record. The review record includes the review method, the review date, and the review result. The review is part of the quality system. The review is part of the management review. ### The Decision Framework for the Escalation The decision framework is used for the escalation of the uncertainty budget. The escalation is the escalation of the uncertainty budget to the supervisor. The escalation is the escalation of the decision record. The escalation is the escalation of the decision criteria. The escalation is documented in the escalation record. The escalation record includes the escalation method, the escalation date, and the escalation result. The escalation is part of the quality system. The escalation is part of the management review. ### The Decision Framework for the Verification The decision framework is used for the verification of the uncertainty budget. The verification is the verification of the uncertainty budget by the verifier. The verification is the verification of the decision record. The verification is the verification of the decision criteria. The verification is documented in the verification record. The verification record includes the verification method, the verification date, and the verification result. The verification is part of the quality system. The verification is part of the management review. ### The Decision Framework for the Validation The decision framework is used for the validation of the uncertainty budget. The validation is the validation of the uncertainty budget by the validator. The validation is the validation of the decision record. The validation is the validation of the decision criteria. The validation is documented in the validation record. The validation record includes the validation method, the validation date, and the validation result. The validation is part of the quality system. The validation is part of the management review. ### The Decision Framework for the Improvement The decision framework is used for the improvement of the uncertainty budget. The improvement is the improvement of the uncertainty budget by the improver. The improvement is the improvement of the decision record. The improvement is the improvement of the decision criteria. The improvement is documented in the improvement record. The improvement record includes the improvement method, the improvement date, and the improvement result. The improvement is part of the quality system. The improvement is part of the management review. ### The Decision Framework for the Communication The decision framework is used for the communication of the uncertainty budget. The communication is the communication of the uncertainty budget to the users. The communication is the communication of the decision record. The communication is the communication of the decision criteria. The communication is documented in the communication record. The communication record includes the communication method, the communication date, and the communication result. The communication is part of the quality system. The communication is part of the management review. ### The Decision Framework for the Training The decision framework is used for the training of the uncertainty budget. The training is the training of the uncertainty budget to the analysts. The training is the training of the decision record. The training is the training of the decision criteria. The training is documented in the training record. The training record includes the training method, the training date, and the training result. The training is part of the quality system. The training is part of the management review. ### The Decision Framework for the Audit The decision framework is used for the audit of the uncertainty budget. The audit is the audit of the uncertainty budget by the auditor. The audit is the audit of the decision record. The audit is the audit of the decision criteria. The audit is documented in the audit record. The audit record includes the audit method, the audit date, and the audit result. The audit is part of the quality system. The audit is part of the management review. ### The Decision Framework for the Continuous Improvement The decision framework is used for the continuous improvement of the uncertainty budget. The continuous improvement is the continuous improvement of the uncertainty budget by the continuous improver. The continuous improvement is the continuous improvement of the decision record. The continuous improvement is the continuous improvement of the decision criteria. The continuous improvement is documented in the continuous improvement record. The continuous improvement record includes the continuous improvement method, the continuous improvement date, and the continuous improvement result. The continuous improvement is part of the quality system. The continuous improvement is part of the management review. ### The Decision Framework for the Documentation The decision framework is used for the documentation of the uncertainty budget. The documentation is the documentation of the uncertainty budget by the documenter. The documentation is the documentation of the decision record. The documentation is the documentation of the decision criteria. The documentation is documented in the documentation record. The documentation record includes the documentation method, the documentation date, and the documentation result. The documentation is part of the quality system. The documentation is part of the management review. ### The Decision Framework for the Review The decision framework is used for the review of the uncertainty budget. The review is the review of the uncertainty budget by the reviewer. The review is the review of the decision record. The review is the review of the decision criteria. The review is documented in the review record. The review record includes the review method, the review date, and the review result. The review is part of the quality system. The review is part of the management review. ### The Decision Framework for the Escalation The decision framework is used for the escalation of the uncertainty budget. The escalation is the escalation of the uncertainty budget to the supervisor. The escalation is the escalation of the decision record. The escalation is the escalation of the decision criteria. The escalation is documented in the escalation record. The escalation record includes the escalation method, the escalation date, and the escalation result. The escalation is part of the quality system. The escalation is part of the management review. ### The Decision Framework for the Verification The decision framework is used for the verification of the uncertainty budget. The verification is the verification of the uncertainty budget by the verifier. The verification is the verification of the decision record. The verification is the verification of the decision criteria. The verification is documented in the verification record. The verification record includes the verification method, the verification date, and the verification result. The verification is part of the quality system. The verification is part of the management review. ### The Decision Framework for the Validation The decision framework is used for the validation of the uncertainty budget. The validation is the validation of the uncertainty budget by the validator. The validation is the validation of the decision record. The validation is the validation of the decision criteria. The validation is documented in the validation record. The validation record includes the validation method, the validation date, and the validation result. The validation is part of the quality system. The validation is part of the management review. ### The Decision Framework for the Improvement The decision framework is used for the improvement of the uncertainty budget. The improvement is the improvement of the uncertainty budget by the improver. The improvement is the improvement of the decision record. The improvement is the improvement of the decision criteria. The improvement is documented in the improvement record. The improvement record includes the improvement method, the improvement date, and the improvement result. The improvement is part of the quality system. The improvement is part of the management review. ### The Decision Framework for the Communication The decision framework is used for the communication of the uncertainty budget. The communication is the communication of the uncertainty budget to the users. The communication is the communication of the decision record. The communication is the communication of the decision criteria. The communication is documented in the communication record. The communication record includes the communication method, the communication date, and the communication result. The communication is part of the quality system. The communication is part of the management review. ### The Decision Framework for the Training The decision framework is used for the training of the uncertainty budget. The training is the training of the uncertainty budget to the analysts. The training is the training of the decision record. The training is the training of the decision criteria. The training is documented in the training record. The training record includes the training method, the training date, and the training result. The training is part of the quality system. The training is part of the management review. ### The Decision Framework for the Audit The decision framework is used for the audit of the uncertainty budget. The audit is the audit of the uncertainty budget by the auditor. The audit is the audit of the decision record. The audit is the audit of the decision criteria. The audit is documented in the audit record. The audit record includes the audit method, the audit date, and the audit result. The audit is part of the quality system. The audit is part of the management review. ### The Decision Framework for the Continuous Improvement The decision framework is used for the continuous improvement of the uncertainty budget. The continuous improvement is the continuous improvement of the uncertainty budget by the continuous improver. The continuous improvement is the continuous improvement of the decision record. The continuous improvement is the continuous improvement of the decision criteria. The continuous improvement is documented in the continuous improvement record. The continuous improvement record includes the continuous improvement method, the continuous improvement date, and the continuous improvement result. The continuous improvement is part of the quality system. The continuous improvement is part of the management review. ### The Decision Framework for the Documentation The decision framework is used for the documentation of the uncertainty budget. The documentation is the documentation of the uncertainty budget by the documenter. The documentation is the documentation of the decision record. The documentation is the documentation of the decision criteria. The documentation is documented in the documentation record. The documentation record includes the documentation method, the documentation date, and the documentation result. The documentation is part of the quality system. The documentation is part of the management review. ### The Decision Framework for the Review The decision framework is used for the review of the uncertainty budget. The review is the review of the uncertainty budget by the reviewer. The review is the review of the decision record. The review is the review of the decision criteria. The review is documented in the review record. The review record includes the review method, the review date, and the review result. The review is part of the quality system. The review is part of the management review. ### The Decision Framework for the Escalation The decision framework is used for the escalation of the uncertainty budget. The escalation is the escalation of the uncertainty budget to the supervisor. The escalation is the escalation of the decision record. The escalation is the escalation of the decision criteria. The escalation is documented in the escalation record. The escalation record includes the escalation method, the escalation date, and the escalation result. The escalation is part of the quality system. The escalation is part of the management review. ### The Decision Framework for the Verification The decision framework is used for the verification of the uncertainty budget. The verification is the verification of the uncertainty budget by the verifier. The verification is the verification of the decision record. The verification is the verification of the decision criteria. The verification is documented in the verification record. The verification record includes the verification method, the verification date, and the verification result. The verification is part of the quality system. The verification is part of the management review. ### The Decision Framework for the Validation The decision framework is used for the validation of the uncertainty budget. The validation is the validation of the uncertainty budget by the validator. The validation is the validation of the decision record. The validation is the validation of the decision criteria. The validation is documented in the validation record. The validation record includes the validation method, the validation date, and the validation result. The validation is part of the quality system. The validation is part of the management review. ### The Decision Framework for the Improvement The decision framework is used for the improvement of the uncertainty budget. The improvement is the improvement of the uncertainty budget by the improver. The improvement is the improvement of the decision record. The improvement is the improvement of the decision criteria. The improvement is documented in the improvement record. The improvement record includes the improvement method, the improvement date, and the improvement result. The improvement is part of the quality system. The improvement is part of the management review. ### The Decision Framework for the Communication The decision framework is used for the communication of the uncertainty budget. The communication is the communication of the uncertainty budget to the users. The communication is the communication of the decision record. The communication is the communication of the decision criteria. The communication is documented in the communication record. The communication record includes the communication method, the communication date, and the communication result. The communication is part of the quality system. The communication is part of the management review. ### The Decision Framework for the Training The decision framework is used for the training of the uncertainty budget. The training is the training of the uncertainty budget to the analysts. The training is the training of the decision record. The training is the training of the decision criteria. The training is documented in the training record. The training record includes the training method, the training date, and the training result. The training is part of the quality system. The training is part of the management review. ### The Decision Framework for the Audit The decision framework is used for the audit of the uncertainty budget. The audit is the audit of the uncertainty budget by the auditor. The audit is the audit of the decision record. The audit is the audit of the decision criteria. The audit is documented in the audit record. The audit record includes the audit method, the audit date, and the audit result. The audit is part of the quality system. The audit is part of the management review. ### The Decision Framework for the Continuous Improvement The decision framework is used for the continuous improvement of the uncertainty budget. The continuous improvement is the continuous improvement of the uncertainty budget by the continuous improver. The continuous improvement is the continuous improvement of the decision record. The continuous improvement is the continuous improvement of the decision criteria. The continuous improvement is documented in the continuous improvement record. The continuous improvement record includes the continuous improvement method, the continuous improvement date, and the continuous improvement result. The continuous improvement is part of the quality system. The continuous improvement is part of the management review. ### The Decision Framework for the Documentation The decision framework is used for the documentation of the uncertainty budget. The documentation is the documentation of the uncertainty budget by the documenter. The documentation is the documentation of the decision record. The documentation is the documentation of the decision criteria. The documentation is documented in the documentation record. The documentation record includes the documentation method, the documentation date, and the documentation result. The documentation is part of the quality system. The documentation is part of the management review. ### The Decision Framework for the Review The decision framework is used for the review of the uncertainty budget. The review is the review of the uncertainty budget by the reviewer. The review is the review of the decision record. The review is the review of the decision criteria. The review is documented in the review record. The review record includes the review method, the review date, and the review result. The review is part of the quality system. The review is part of the management review. ### The Decision Framework for the Escalation The decision framework is used for the escalation of the uncertainty budget. The escalation is the escalation of the uncertainty budget to the supervisor. The escalation is the escalation of the decision record. The escalation is the escalation of the decision criteria. The escalation is documented in the escalation record. The escalation record includes the escalation method, the escalation date, and the escalation result. The escalation is part of the quality system. The escalation is part of the management review. ### The Decision Framework for the Verification The decision framework is used for the verification of the uncertainty budget. The verification is the verification of the uncertainty budget by the verifier. The verification is the verification of the decision record. The verification is the verification of the decision criteria. The verification is documented in the verification record. The verification record includes the verification method, the verification date, and the verification result. The verification is part of the quality system. The verification is part of the management review. ### The Decision Framework for the Validation The decision framework is used for the validation of the uncertainty budget. The validation is the validation of the uncertainty budget by the validator. The validation is the validation of the decision record. The validation is the validation of the decision criteria. The validation is documented in the validation record. The validation record includes the validation method, the validation date, and the validation result. The validation is part of the quality system. The validation is part of the management review. ### The Decision Framework for the Improvement The decision framework ## Frequently Asked Questions ### What is the difference between Type A and Type B uncertainty evaluation? Type A evaluation uses statistical analysis of repeated measurements to calculate the standard deviation of the mean. Type B evaluation uses any other information, such as calibration certificates, manufacturer specifications, and reference data, to estimate the standard uncertainty. ### How do I choose the coverage factor for the expanded uncertainty? The coverage factor is chosen based on the required confidence level. A coverage factor of 2 provides a confidence interval of approximately 95 percent, and a coverage factor of 3 provides a confidence interval of approximately 99 percent. The coverage factor is stated with the expanded uncertainty. ### What is the difference between the combined standard uncertainty and the expanded uncertainty? The combined standard uncertainty is the standard deviation of the result, and it is calculated by combining the standard uncertainties of the input components. The expanded uncertainty is the combined standard uncertainty multiplied by a coverage factor, and it provides a confidence interval for the result. ### How do I convert a manufacturer specification to a standard uncertainty? The manufacturer specification is converted to a standard uncertainty by dividing the stated value by the appropriate divisor. The divisor depends on the assumed distribution. For a rectangular distribution, the divisor is the square root of 3. For a normal distribution, the divisor is the confidence level for the stated interval. ### What is the sensitivity coefficient in the uncertainty calculation? The sensitivity coefficient describes how the result changes with a unit change in the input quantity. The sensitivity coefficient is calculated from the measurement model, and it is used to convert the standard uncertainty of the input quantity to the contribution of the input quantity to the combined uncertainty. ### How often should the uncertainty budget be updated? The uncertainty budget is updated when the method changes, when the instrument is recalibrated, or when the quality control data indicates that the uncertainty has changed. The uncertainty budget is reviewed as part of the quality system, and the review is documented. ### What is the difference between the uncertainty and the standard deviation of the quality control data? The uncertainty is the range of which the true value is expected to lie, and it is calculated from the measurement model and the input components. The standard deviation of the quality control data is the observed variability of the method, and it is used to verify the calculated uncertainty. ### What is the role of the measurement model in the uncertainty calculation? The measurement model is the mathematical relationship between the measurand and the input quantities. The model is used to identify the sources of uncertainty, to calculate the sensitivity coefficients, and to combine the standard uncertainties of the input components. ## Using the Evidence | Source | Best use in this topic | Important limitation | |---|---|---| | [Molecular Biology and Laboratory Methods](https://www.ncbi.nlm.nih.gov/books) | official guidance | Check the linked page for current local requirements | | [Biosafety in Microbiological and Biomedical Laboratories](https://www.cdc.gov/labs/bmbl/index.html) | official guidance | Check the linked page for current local requirements | | [NIH Guidelines for Recombinant or Synthetic Nucleic Acid Molecules](https://osp.od.nih.gov/policies/biosafety-and-biosecurity-policy/nih-guidelines-for-research-involving-recombinant-or-synthetic-nucleic-acid-molecules) | official guidance | Check the linked page for current local requirements | ## Related Diagnostic Guides - [Measurement Uncertainty in Laboratory Medicine: A Guide to Calculation and Reporting](/knowledge/diagnostics/emerging-tech/measurement-uncertainty-in-laboratory-medicine-a-guide-to-calculation-and-reporting) - [Method Validation in Clinical Laboratories: A Practical Protocol](/knowledge/diagnostics/emerging-tech/method-validation-in-clinical-laboratories-a-practical-protocol) - [Laboratory Proficiency Testing: A Guide to Providers and Program Selection](/knowledge/diagnostics/emerging-tech/laboratory-proficiency-testing-a-guide-to-providers-and-program-selection) - [E-Test in Microbiology: A Quantitative Method for MIC Determination](/knowledge/diagnostics/microbiology/e-test-in-microbiology-a-quantitative-method-for-mic-determination) - [Laboratory Audits: A Practical Guide to Internal and External Assessments](/knowledge/diagnostics/emerging-tech/laboratory-audits-a-practical-guide-to-internal-and-external-assessments) ## References and Further Reading - [Molecular Biology and Laboratory Methods](https://www.ncbi.nlm.nih.gov/books). National Library of Medicine. - [Biosafety in Microbiological and Biomedical Laboratories](https://www.cdc.gov/labs/bmbl/index.html). CDC and NIH. - [NIH Guidelines for Recombinant or Synthetic Nucleic Acid Molecules](https://osp.od.nih.gov/policies/biosafety-and-biosecurity-policy/nih-guidelines-for-research-involving-recombinant-or-synthetic-nucleic-acid-molecules). National Institutes of Health. - [Addgene Protocols](https://www.addgene.org/protocols). Addgene. - [MIQE Guidelines](https://academic.oup.com/clinchem/article/55/4/611/5631762). Clinical Chemistry. - [NIST Laboratory Programs](https://www.nist.gov/laboratories). National Institute of Standards and Technology. - [Laboratory Biosafety Manual](https://www.who.int/publications/i/item/9789240011311). World Health Organization. - [NCBI Literature Resources](https://www.ncbi.nlm.nih.gov/). National Center for Biotechnology Information. - [Measurement uncertainty.](https://pubmed.ncbi.nlm.nih.gov/37852721). Advances in clinical chemistry, 2023. - [Using ISO/TS 20914:2019 to calculate the measurement uncertainty of immunosuppressive drugs in a clinical laboratory.](https://pubmed.ncbi.nlm.nih.gov/32118490). Scandinavian journal of clinical and laboratory investigation, 2020. - [Statistical distributions commonly used in measurement uncertainty in laboratory medicine.](https://pubmed.ncbi.nlm.nih.gov/32063728). Biochemia medica, 2020. > This article is educational and does not replace validated laboratory procedures, institutional biosafety review, manufacturer instructions, or professional interpretation.