Pre-thesis checklist

By Dr. Zubair Khalid, DVM, MS, PhD · 2026-08-27

Quick Answer

• Work through a 20-item pre-thesis checklist covering objectives, methods, resources, ethics, data management, and piloting before you begin formal writing.
• Select reporting guidelines from the EQUATOR Network early because they shape your methods, analysis, and presentation choices from the start.
• Treat the checklist as a planning tool, not a guarantee of approval, since institutional policies and funder requirements vary by program and jurisdiction.

At a Glance

Why a Pre-Thesis Checklist Matters

A thesis project combines intellectual ambition with operational complexity. Students often focus on the research question and postpone decisions about methods, data handling, and compliance until problems surface. That sequence creates avoidable delays and, in some cases, prevents completion altogether.

The pre-thesis period is the time to align your project with external expectations. Funding agencies, journals, and institutions each maintain standards that affect how you design, conduct, and report your work. The National Institutes of Health, for example, expects applicants to understand grant policies and application requirements before submitting a proposal, and the same logic applies to thesis planning. You need to know what your institution and any funding body require before you commit to a design.

A checklist serves a practical function. It converts abstract advice about rigor into concrete actions you can take in a specific order. Each item on the checklist forces a decision, and each decision produces a record you can use later in your methods chapter, ethics application, or data management plan.

Core Principles of Thesis Planning

Align Objectives With Feasibility

Your thesis objective must be answerable within your timeframe, budget, and skill level. A broad question such as "How does nutrition affect animal health?" cannot be answered in a single project. A focused question such as "Does a specific feed additive alter weight gain in weaned piglets over a six-week period?" defines a measurable outcome and a clear endpoint.

Write your objective as a statement that includes the population, the intervention or exposure, the comparator, and the outcome. This structure helps you identify the data you need and the analysis you will run. If you cannot specify these elements, the objective is not yet ready for implementation.

Match Methods to the Question

The method must follow from the question, not the reverse. A descriptive question about prevalence requires a survey or observational design. A question about cause and effect requires an experiment with controls and randomization where feasible. A question about diagnostic accuracy requires a comparison against a reference standard.

The EQUATOR Network maintains a collection of reporting guidelines that correspond to different study designs. These guidelines tell you what information to include in your final report, but they also help you plan. If a guideline asks for details about blinding, randomization, or sample size, you need to build those elements into your protocol before data collection begins.

Build Ethics Into the Design

Ethical review is not a formality. It is a design check that protects participants, animals, and the integrity of the research. Institutional review boards and animal care committees evaluate whether your methods minimize harm, whether consent or approval processes are adequate, and whether the scientific value justifies the risks.

The Committee on Publication Ethics describes core practices that apply throughout the research lifecycle, including ethical oversight, data handling, and authorship. Review these practices before you start so your project complies with expectations that extend beyond your institution. If your study involves animals, humans, or biological samples, confirm which approvals are required and how long the review process takes at your institution.

The 20-Item Pre-Thesis Checklist

Domain 1: Objectives and Scope

Item 1. Define the research question in one sentence. Write the question as a testable statement. If you cannot state it in one sentence, refine it until you can.

Item 2. Specify the study population and setting. Identify the animals, samples, or subjects you will study and where you will recruit or obtain them. Include inclusion and exclusion criteria.

Item 3. State the primary outcome and secondary outcomes. Choose one primary outcome that answers the research question. Secondary outcomes provide supporting information but do not drive the sample size calculation.

Item 4. Document the scope boundaries. List what the thesis will not cover. This prevents scope creep and gives you a defensible answer when reviewers ask why you excluded a related topic.

Domain 2: Methods and Reporting

Item 5. Select a reporting guideline. Use the EQUATOR Network to identify the guideline that matches your study design. For randomized trials, use the appropriate trial reporting guideline. For observational studies, use the corresponding reporting guideline. For systematic reviews, use the review reporting guideline.

Item 6. Register the study if required. Some journals and funders require prospective registration for clinical trials and systematic reviews. Check the requirements for your field and register before data collection if applicable.

Item 7. Write a detailed protocol. The protocol should describe the design, procedures, measurements, and analysis plan in enough detail that another researcher could replicate the study.

Item 8. Define the sample size and justify it. State how you calculated the sample size and what assumptions you used. If you cannot calculate a formal sample size, explain the practical constraints that determine the number of observations.

Domain 3: Resources and Feasibility

Item 9. Confirm equipment and facility access. Verify that the instruments, animal housing, laboratory space, or field sites you need are available for the duration of your project.

Item 10. Secure funding and supplies. Itemize the costs of consumables, animal care, shipping, sequencing, or other expenses. Confirm which costs your department or grant covers and which you must fund yourself.

Item 11. Establish a timeline with milestones. Break the project into phases such as ethics approval, piloting, data collection, analysis, and writing. Assign realistic dates to each phase and build in buffer time for delays.

Item 12. Confirm supervisory support. Meet with your supervisor to review the project plan, agree on meeting frequency, and clarify how decisions will be made when problems arise.

Domain 4: Ethics and Compliance

Item 13. Identify all required approvals. Determine whether your study needs institutional review board approval, animal care and use committee approval, biosafety clearance, or other permissions. Start these applications early because review can take weeks or months.

Item 14. Complete required training. Many institutions require training in responsible conduct of research, animal care, biosafety, or data handling before you begin. Complete these courses and keep certificates on file.

Item 15. Check funder and institutional policies. Review the policies of any funding agency and your institution regarding data sharing, authorship, and publication. The NIH Data Management and Sharing Policy describes expectations for NIH-funded research, and similar policies may apply to your project.

Domain 5: Data Management

Item 16. Write a data management plan. Describe what data you will collect, how you will organize and store it, who can access it, and how long you will preserve it. The NIH Data Management and Sharing Policy provides a framework for these decisions, and your institution may have its own template.

Item 17. Establish a backup system. Set up automatic backups for electronic data and a secure storage location for physical samples and paper records. Test the backup system before you collect irreplaceable data.

Item 18. Define file naming and version control. Agree on a naming convention for files and a system for tracking versions. This prevents confusion when multiple people work on the same dataset or when you revise analysis scripts.

Domain 6: Piloting and Risk

Item 19. Conduct a pilot study. Test your protocol on a small number of subjects or samples before full data collection. Record what goes wrong, what takes longer than expected, and what measurements are unclear.

Item 20. Revise the protocol based on pilot results. Update the protocol, timeline, and budget based on what you learned. Document the changes and the reasons for them so your methods chapter reflects the final procedures.

Practical Implementation Steps

Step 1: Complete the Checklist in Order

Work through the checklist from item 1 to item 20. The order matters because later items depend on earlier decisions. You cannot write a data management plan until you know what data you will collect, and you cannot apply for ethics approval until you have defined your methods.

Step 2: Create a Planning Document

Write each checklist item as a heading in a single document. Under each heading, record your decision, the date, and any supporting information. This document becomes the foundation for your thesis introduction, methods chapter, and ethics application.

Step 3: Review the Checklist With Your Supervisor

Schedule a meeting to review your completed checklist with your supervisor before you begin data collection. Ask specifically about items that are uncertain, such as sample size justification, reporting guideline selection, and institutional requirements.

Step 4: Store the Checklist With Your Study Records

Keep the checklist and planning document with your ethics approval, protocol, and data management plan. This creates a complete record of your planning decisions that you can reference during writing and defense.

Records and Measurements

What to Record During Planning

Maintain a planning log that captures the date of each decision, the rationale, and any changes made after review. This log is valuable when you write your methods chapter because it documents why you chose a particular design or sample size.

Record the following items in your planning log:

• The research question and its revisions
• The reporting guideline selected and the date of selection
• The sample size calculation and its assumptions
• The ethics approval application date and approval date
• The pilot study dates and observed problems
• The data management plan version and revision dates

How to Measure Planning Progress

Use the checklist itself as a progress tracker. Mark each item complete only when you have written evidence of the decision. For example, item 5 is complete when you have selected a specific reporting guideline and noted it in your planning document, not when you have thought about reporting guidelines in general.

Common Failure Patterns

Starting Data Collection Before Ethics Approval

Students sometimes begin pilot work or preliminary observations before receiving ethics approval, assuming that informal data collection does not require review. This assumption can invalidate the data and delay the entire project. Confirm the approval status before any data collection, including pilot work.

Selecting Methods Without a Reporting Guideline

Choosing a study design without consulting the relevant reporting guideline leads to missing information in the final thesis. Reviewers and examiners notice when randomization procedures, blinding, or eligibility criteria are not described. Select the guideline during planning and use it as a checklist for your methods chapter.

Underestimating Data Management Effort

Students often focus on data collection and postpone decisions about storage, backup, and sharing. This leads to lost files, unclear ownership, and difficulty complying with funder requirements. Write the data management plan before you collect data and test your backup system early.

Skipping the Pilot Study

A pilot study is the cheapest way to find problems in your protocol. Skipping it to save time usually costs more time later when measurements fail, equipment malfunctions, or procedures take longer than planned. Run a pilot even if it is small.

Ignoring Funder and Journal Policies

Funding agencies and journals have policies about data sharing, authorship, and reporting that affect your thesis. The NIH Data Management and Sharing Policy, for example, describes expectations for NIH-funded research, and journals increasingly require reporting guideline adherence. Review these policies during planning, not after analysis.

Limitations and Professional Judgment

Institutional Variation

The checklist describes general planning steps, but specific requirements vary by institution, department, and program. Your graduate handbook, department coordinator, or supervisor can clarify which approvals, training, and formats apply to your project. The checklist does not replace those institutional requirements.

Jurisdiction-Specific Requirements

Research involving animals, humans, or biological samples is regulated differently across jurisdictions. The checklist identifies the need for approvals but does not specify which approvals apply in your location. Consult your institution's compliance office for jurisdiction-specific requirements.

Funder-Specific Policies

The NIH policies referenced in this article apply to NIH-funded research. If your funding comes from another agency, a private foundation, or your department, review that funder's policies separately. The checklist helps you identify the need to review policies but does not substitute for reading the actual policy documents.

When to Escalate to a Professional

Seek professional advice from your supervisor, department chair, or institutional compliance office when you encounter any of the following situations:

• You are unsure whether your study requires ethics approval or which committee reviews it
• Your funder requires data sharing or management practices that you do not understand
• Your pilot study reveals problems that require a major design change
• You discover that a required approval will delay your timeline beyond your program deadline
• You have questions about authorship, data ownership, or publication that your supervisor cannot answer

Welfare and Safety Context

Animal Welfare Considerations

If your thesis involves animals, the design must minimize pain, distress, and the number of animals used. Your animal care and use committee evaluates whether the scientific value justifies the animal use and whether the procedures are humane. Plan for appropriate housing, enrichment, analgesia, and euthanasia methods as part of the protocol.

Human Participant Protections

If your thesis involves human participants, including surveys, interviews, or biological samples, you must obtain informed consent and protect participant privacy. The institutional review board evaluates whether the risks are minimal and whether the consent process is adequate. Plan for secure data storage and de-identification where possible.

Laboratory and Field Safety

Biological samples, chemicals, and field sites present physical hazards. Confirm that you have completed required safety training and that your protocol includes appropriate personal protective equipment and emergency procedures. Your institution's environmental health and safety office can advise on specific requirements.

Decision Framework for Thesis Planning Trade-Offs

The Feasibility Matrix

A thesis plan often fails not because individual decisions are wrong, but because decisions conflict with each other. You may have a sound research question that requires more animals than your budget allows, or a rigorous sampling plan that extends beyond your program deadline. The feasibility matrix gives you a structured way to resolve these conflicts before they become crises.

Create a simple table with your checklist items as rows and four columns: scientific value, cost, time, and risk. For each item, assign a rating of low, medium, or high. The matrix reveals where your plan is out of balance. A study with high scientific value, high cost, high time demand, and high risk needs revision before you commit resources. A study with medium value, low cost, low time demand, and low risk may be too modest to justify a thesis.

The matrix works best when you complete it with your supervisor. Your supervisor can challenge your ratings and point out costs or risks you have not considered. The National Institutes of Health grant application process uses a similar logic, asking applicants to justify the significance, innovation, and approach of their proposed work within the constraints of the funding mechanism. Your thesis plan should withstand the same scrutiny.

The Decision Rule for Scope Reduction

When the matrix reveals an imbalance, you need a rule for deciding what to cut. The rule is to preserve the primary outcome and cut secondary aims. Your primary outcome answers the research question and drives the sample size calculation. Secondary outcomes provide supporting information but do not define the study. If you must reduce scope, remove secondary outcomes first, then reduce the number of subgroups or time points, and only as a last resort change the primary outcome or study design.

Document every scope reduction in your planning log. Record what you cut, why you cut it, and who approved the change. This record protects you during your thesis defense when examiners ask why you did not measure a particular variable or include a particular group.

The Contingency Budget

Every thesis plan needs a contingency budget for time, money, and animals. A common error is planning for the best case where equipment works, animals remain healthy, and protocols run on schedule. Field research, laboratory work, and animal studies rarely follow the best case.

Build a contingency of 20 to 30 percent into your timeline for each major phase. If you estimate eight weeks for data collection, plan for ten. If your budget covers 40 animals, confirm you can afford 48 or that you can complete the study with fewer if losses occur. The contingency budget is not pessimism. It is a realistic acknowledgment that pilot studies reveal problems, equipment fails, and animals become ill or die.

The Go or No-Go Decision Point

Before you begin full data collection, schedule a formal go or no-go review. This review uses the pilot study results, the feasibility matrix, and the contingency budget to decide whether the project proceeds as planned, proceeds with modifications, or stops.

The review should answer three questions. First, did the pilot study produce usable data that matches the planned analysis? Second, did the actual costs and time match the estimates in the feasibility matrix? Third, are the remaining risks manageable within the contingency budget?

If the answer to any question is no, you have three options. You can modify the protocol and run another pilot. You can reduce the scope using the decision rule described above. Or you can stop the project and develop a new research question. Stopping is difficult, but it is cheaper than collecting a full dataset that cannot answer the research question.

The Decision Log

A decision log is a dated record of every significant choice you make during thesis planning. It differs from the planning document in one important way. The planning document records what you decided. The decision log records why you decided it and what alternatives you considered.

For each entry, write the date, the decision, the alternatives you rejected, the reason for the choice, and the source of any information that informed the decision. If you chose a sample size of 30 based on a power calculation, record the calculation and its assumptions. If you rejected a different study design because it required more animals than your budget allowed, record that reasoning.

The decision log serves two purposes. During the project, it helps you stay consistent when new information emerges. If a reviewer questions your methods, you can show the reasoning behind each choice. During writing, it becomes the raw material for your methods chapter and your limitations section. The Committee on Publication Ethics describes transparency as a core practice in research, and a decision log is a practical way to build transparency into your own work.

When to Apply the Framework

Apply the feasibility matrix after you complete the 20-item checklist and before you begin the pilot study. The matrix may reveal problems that you can fix in the protocol before you spend time and money on piloting. Apply the go or no-go review after the pilot study and before full data collection. This is the last point where you can change direction without wasting a full dataset.

Common Failure Patterns in Decision Making

The most common failure is making decisions in isolation. A student chooses a sample size without checking whether the budget covers the associated animal costs, or selects a statistical analysis without confirming the data collection method can produce the required measurements. The feasibility matrix prevents this by forcing you to consider cost, time, and risk together.

A second failure is treating the pilot study as optional. The pilot is not a rehearsal. It is the primary source of evidence for your go or no-go decision. Without pilot data, you are making the most important decision in your project without evidence.

A third failure is refusing to stop a project that is not working. Students often continue because they have invested time in the planning or because they fear disappointing their supervisor. The go or no-go review gives you a structured, defensible way to make the stop decision before you invest in full data collection.

Escalation Criteria for the Decision Framework

Escalate to your supervisor or department chair when the feasibility matrix shows that the project cannot be completed within your program timeline, when the pilot study reveals problems that require a fundamental design change, or when you and your supervisor disagree about whether to proceed. Your institution may have formal procedures for changing thesis topics or extending deadlines. Consult your graduate handbook or department coordinator for the specific process in your program.

Frequently Asked Questions

How long before data collection should I start the pre-thesis checklist?

Start the checklist at least three months before your planned data collection start date. Ethics approval, training completion, and equipment confirmation can each take weeks, and the pilot study adds additional time. Starting early gives you room to resolve problems without delaying your timeline.

What is the most common mistake students make in thesis planning?

The most common mistake is starting data collection before completing the planning steps, particularly ethics approval and piloting. This creates the risk of invalid data, noncompliance, and expensive rework. Completing the checklist in order prevents this failure pattern.

Do I need to register my thesis study before data collection?

Registration requirements depend on your field and the study design. Clinical trials and systematic reviews often require prospective registration, and some journals will not publish unregistered studies. Check the requirements for your specific design and target journals during the planning phase.

How do I choose the right reporting guideline for my thesis?

Use the EQUATOR Network to search for guidelines by study design. The network provides a searchable database of reporting guidelines with descriptions of the designs they apply to. Select the guideline that matches your primary design and use it to structure your methods and results sections.

What should I do if my pilot study reveals major problems?

Document the problems and the changes you make in response. Revise your protocol, timeline, and budget accordingly. If the problems require a fundamental design change, consult your supervisor before proceeding. A pilot study that reveals problems is a success because it prevents those problems from affecting your full dataset.

How detailed should my data management plan be?

Your data management plan should describe what data you collect, the file formats, the storage and backup systems, who has access, and how long you will preserve the data. If your funder has a specific data management policy, follow that policy's requirements. The NIH Data Management and Sharing Policy provides a useful framework even if your funding is not from NIH.

Can I use the same checklist for a master's thesis and a doctoral dissertation?

Yes, the checklist applies to both, but the depth of each item may differ. A doctoral dissertation typically requires a more extensive methods section, a larger sample size, and a more detailed data management plan. The checklist ensures you address each domain regardless of the degree level.

What should I do if my supervisor disagrees with a checklist decision?

Discuss the disagreement and document the resolution. Your supervisor has knowledge of your program's requirements and the expectations in your field. If you cannot reach agreement, consult your department chair or graduate coordinator for guidance on the appropriate resolution process.

Using the Evidence

Related Articles

• Bioinformatics Careers: What You Need to Know Before You Start
• Cross-Sectional Study Limitations: What You Need to Know Before You Start
• Feasibility of a Research Study: How to Assess Before You Start
• Variant Calling Workflow: Design Decisions Before You Start
• Data Lifecycle Management in Research: From Collection to Preservation

References and Further Reading

• Research Methods Resources. National Library of Medicine.
• EQUATOR Network. EQUATOR Network.
• Core Practices. Committee on Publication Ethics.
• NIH Grants and Funding. National Institutes of Health.
• ORCID for Researchers. ORCID.
• Data Management and Sharing Policy. National Institutes of Health.
• NCBI Literature Resources. National Center for Biotechnology Information.
• PubMed. National Library of Medicine.

This article is educational and does not replace institutional policy, professional advice, or applicable safety and regulatory requirements.