13. Objectives

Explaining the purpose of the study by describing the question(s) that the research addresses, allows readers to determine if the study is relevant to them. Readers can also assess the relevance of the model organism, procedures, outcomes measured, and analysis used.

Knowing if a study is exploratory or hypothesis-testing is critical to its interpretation. A typical exploratory study may measure multiple outcomes and look for patterns in the data, or relationships that can be used to generate hypotheses. It may also be a pilot study which aims to inform the design or feasibility of larger subsequent experiments. Exploratory research helps researchers to design hypothesis-testing experiments, by choosing what variables or outcome measures to focus on in subsequent studies.

Testing a specific hypothesis has implications for both the study design and the data analysis [1,2]. For example, an experiment designed to detect a hypothesised effect will likely need to be analysed with inferential statistics, and a statistical estimation of the sample size will need to be performed a priori (see item 2 – Sample size). Hypothesis-testing studies also have a pre-defined primary outcome measure, which is used to assess the evidence in support of the specific research question (see item 6 – Outcome measures).

In contrast, exploratory research investigates many possible effects, and is likely to yield more false positive results because some will be positive by chance. Thus results from well-designed hypothesis-testing studies provide stronger evidence than those from exploratory or descriptive studies. Independent replication and meta-analysis can further increase the confidence in conclusions.

Clearly outline the objective(s) of the study, including whether it is hypothesis-testing or exploratory, or if it includes research of both types. Hypothesis-testing studies may collect additional information for exploratory purposes, it is important to distinguish which hypotheses were prespecified and which originated after data inspection, especially when reporting unanticipated effects or outcomes that were not part of the original study design.

References

1. Festing MF and Altman DG (2002). Guidelines for the design and statistical analysis of experiments using laboratory animals. ILAR journal. http://www.ncbi.nlm.nih.gov/pubmed/12391400
2. Kimmelman J, Mogil JS and Dirnagl U (2014). Distinguishing between exploratory and confirmatory preclinical research will improve translation. PLoS Biol. doi: 10.1371/journal.pbio.1001863