odr-package: Optimal Design and Statistical Power for Experimental Studies...

In odr: Optimal Design and Statistical Power for Experimental Studies Investigating Main, Mediation, and Moderation Effects

Optimal Design and Statistical Power for Experimental Studies Investigating Main, Mediation, and Moderation Effects

Description

This package is to help researchers design cost-efficient and well-powered experimental studies investigating main, mediation, and moderation effects (and some combinations). Specifically, this package can (a) identify optimal sample allocations, (b) compare design efficiency between different sample allocations, and (c) perform power analyses with and without accommodating costs and budget.

Details

The package covers seven types of experiments aiming to detect main, moderation, and mediation effects. These experiments are individual randomized controlled trials (RCTs), two-, three-, and four-level cluster-randomized trials (CRTs), two-, three-, and four-level multisite randomized trials (MRTs). The two categorical functions are 'od' and 'power'. The 'od' function can calculate the optimal sample allocation with and without constraint for each type of experiments. The 'power' function by default can calculate required budget (and required sample size) for desired power, minimum detectable effect size (MDES) under a fixed budget, statistical power under a fixed budget. The 'power' function can perform conventional power analyses (e.g., required sample size, power, MDES calculation). The uniform function 're' (or 'rpe') is to compare the relative (precision and) efficiency between two designs with different sample allocations (limited to main effects).

Author(s)

Zuchao Shen, Benjamin Kelcey

Maintainer: Zuchao Shen [e-mail] (University of Georgia)

odr documentation built on Aug. 8, 2023, 5:13 p.m.