study-design

An application designed to help researchers and managers plan animal tracking projects tailored to their specific research questions.

Prioritize variables in observational study design through the joint variable importance plot; shiny app: https://ldliao.shinyapps.io/jointVIP/

An interactive skill that works with you while answering a causal question

One workflow for sport-science writing: topic selection, analysis and figures, human-voice writing checks, and live Zotero citations in Word (zh / en)

AWARE is a decision support tool for Avoiding WAste in health REsearch. It allows users to upload studies and assess their value for decision-making. In development.

Study definitions describing the tasks, surveys, and schedules of the My Heart Counts cardiovascular health study.

This course is designed to help researchers understand clinical data, covering questions such as: Where does clinical data come from? What makes it unique? What are special considerations for its handling and management?

R code for Wintermantel et al. — Equivalence testing in pesticide risk assessment: Evaluation and practical guidance for design, analysis and interpretation (Environment International).

Davis, K. L., Silverman, E. D., Sussman, A. L., Wilson, R. R., Zipkin, E. F. (2022). Errors in aerial survey count data: Identifying pitfalls and solutions. Ecology and Evolution 12:e8733.

Can this design detect the effect it is looking for? Simulation-based power, minimum designs, and detection ceilings for precision psychotherapy studies under therapist nesting.

A Shiny app for designing spatially explicit capture–recapture studies

Updated version

Pre-data recovery tests for planned study designs: simulate whether a planned design-analysis pair can recover its target estimand, with PASS/RISK/FAIL verdicts under versioned threshold profiles. Companion R package to the recovery-test methods paper.

Literature and simulation (using R) resources for the study design and statistical analysis of RAND/UCLA Method (RAM) consensus studies.

Sample size estimation for single cell studies

Python mirror of recoverlite: pre-data recovery tests for planned study designs (protocol-identical to the R package; results agree within Monte Carlo error)

The case time series design

CC0 open study designs for measurement scope gaps, with self-graded embedding geometry and cut-recoverability experiments

Clinical study design (D1-D5): falsifiable hypotheses, sample size, feasibility, ethics

This repository showcases key study designs used in public health research, providing a practical, hands-on learning resource for students and early-career researchers. It covers the full research workflow—from problem definition and study design to statistical analysis and interpretation—using structured examples and synthetic datasets.