Statistical power and false positive rates for interdependent outcomes are strongly influenced by test type: Implications for behavioral neuroscience.

ABSTRACT: Statistical errors in preclinical science are a barrier to reproducibility and translation. For instance, linear models (e.g., ANOVA, linear regression) may be misapplied to data that violate assumptions. In behavioral neuroscience and psychopharmacology, linear models are frequently applied to interdependent or compositional data, which includes behavioral assessments where animals concurrently choose between chambers, objects, outcomes, or types of behavior (e.g., forced swim, novel object, place/social preference). The current study simulated behavioral data for a task with four interdependent choices (i.e., increased choice of a given outcome decreases others) using Monte Carlo methods. 16,000 datasets were simulated (1000 each of 4 effect sizes by 4 sample sizes) and statistical appro

SUBMITTER: Frankot M 

PROVIDER: S-EPMC10516944 | biostudies-literature | 2023 Oct

REPOSITORIES: biostudies-literature