Multistudy

Multistudy is a research approach in which multiple separate studies are conducted to investigate a single research question or hypothesis. A multistudy project may be conducted within one laboratory or across multiple labs, and is designed to assess robustness and generalizability across samples, tasks, or settings. It is commonly used in psychology, social sciences, health research, and market research, where single experiments can be influenced by sampling or methodological artifacts.

In practice, a multistudy project includes a preregistered plan with a shared core hypothesis and analysis protocol, though each study is typically powered to detect effects on its own. Studies may use identical procedures across contexts or vary key elements to test boundary conditions. Independent samples or laboratories are often employed to reduce non-independence. Results are reported for each study and then synthesized, typically through meta-analytic methods or random-effects models to estimate an overall effect and to quantify heterogeneity.

Advantages include increased confidence in findings through replication and generalizability, reduced risk of p-hacking, and more accurate assessment of ecological validity. Limitations can include higher resource demands, potential publication bias if some studies fail to reproduce effects, and complexity in coordinating reporting across studies. Best practices emphasize preregistration, transparent reporting of all studies, adequate power, and clear, preregistered analysis plans.

See also: replication, meta-analysis, preregistration, multi-lab collaboration.