Study design, controls, and reproducibility
Research methodology
A practical framework for converting a research question into a controlled, documented, and interpretable laboratory study.
Academy briefing 02
Key takeaways
- Define the hypothesis, model, endpoints, and analysis before data collection.
- Use controls to separate the variable of interest from background effects.
- Record enough detail for an independent researcher to evaluate and repeat the work.
01
Start with a precise question
A strong study begins with a falsifiable question and a pre-specified hypothesis. The chosen model, observations, and analytical method should directly address that question rather than merely generate data.
Define primary and secondary endpoints in advance. Establish inclusion and exclusion criteria, expected sources of variation, and a plan for handling missing or anomalous observations before results are known.
02
Controls and comparison groups
Negative controls establish background response, vehicle controls isolate effects of the delivery matrix, and positive controls confirm that the system and method can detect an expected signal. Blank and reference samples can also reveal contamination, carryover, or analytical drift.
Control selection should match the model and method. A control that does not experience the same preparation, handling, and measurement steps may fail to isolate the intended variable.
03
Bias, randomization, and replication
Random assignment reduces systematic allocation bias, while blinding can reduce conscious and unconscious influence during measurement or interpretation. Technical replicates assess method precision; independent biological replicates address variation across experimental units.
Sample-size planning should be based on the expected effect, variability, acceptable error rates, and analysis plan. More measurements do not correct a biased design.
04
Documentation and reproducibility
A complete research record connects each result to the protocol version, operator, date, instrument, raw data, material batch, preparation record, and analysis method. Changes should be traceable rather than overwritten.
Reproducibility improves when protocols define critical steps, acceptance criteria, calibration requirements, and data-processing decisions. Deviations and failed runs are part of the scientific record and should be documented.
Reference desk
Essential terms
- Endpoint
- A pre-defined outcome used to answer the research question.
- Confounder
- A variable related to both the studied factor and the measured outcome.
- Replication
- Independent repetition used to evaluate the consistency of an observation.
- Reproducibility
- The ability to obtain consistent conclusions when a study is repeated or reanalyzed.
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