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odr (version 1.4.4)

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

Description

Calculate the optimal sample size allocation that produces the highest statistical power for experimental studies under a budget constraint, and perform power analyses with and without accommodating cost structures of sampling. The designs cover single-level and multilevel experiments detecting main, mediation, and moderation effects (and some combinations). The references for the proposed methods include: (1) Shen, Z., & Kelcey, B. (2020). Optimal sample allocation under unequal costs in cluster-randomized trials. Journal of Educational and Behavioral Statistics, 45(4): 446-474. . (2) Shen, Z., & Kelcey, B. (2022b). Optimal sample allocation for three-level multisite cluster-randomized trials. Journal of Research on Educational Effectiveness, 15 (1), 130-150. . (3) Shen, Z., & Kelcey, B. (2022a). Optimal sample allocation in multisite randomized trials. The Journal of Experimental Education. . (4) Champely, S. (2020). pwr: Basic functions for power analysis (Version 1.3-0) [Software]. Available from .

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Version

Install

install.packages('odr')

Monthly Downloads

192

Version

1.4.4

License

GPL-3

Maintainer

Zuchao Shen

Last Published

August 8th, 2023

Functions in odr (1.4.4)

od.2m

Optimal sample allocation calculation for two-level MRTs detecting main effects
od.4

Optimal sample allocation calculation for four-level CRTs detecting main effects
od.2m.111

Optimal sample allocation calculation for two-level multisite-randomized trials investigating mediation effects with individual-level mediators (1-1-1)
od.1.111

Optimal sample allocation calculation for single-level randomized controlled trials (RCTs) investigating mediation effects (1-1-1)
od.1

Optimal sample allocation calculation for single-level experiments detecting main effects
od.2.221

Optimal sample allocation calculation for two-level CRTs probing mediation effects with cluster-level mediators
od.3m

Optimal sample allocation calculation for three-level MRTs detecting main effects
gen.design.pars

Generate optimal design parameters using ant colony optimization
od.2

Optimal sample allocation calculation for two-level CRTs detecting main effects
od.3

Optimal sample allocation calculation for three-level CRTs detecting main effects
od.4m

Optimal sample allocation calculation for four-level MRTs detecting main effects
power.2m.111

Budget and/or sample size, power, MDES calculation for MRTs investigating mediation effects with individual-level mediators
power.3

Budget and/or sample size, power, MDES calculation for three-level CRTs detecting main effects
power.1.111

Budget and/or sample size, power, MDES calculation for MRTs investigating mediation effects with individual-level mediators
power.2.221

Budget and/or sample size, power calculation for CRTs probing mediation effects with cluster-level mediators
power.2m

Budget and/or sample size, power, MDES calculation for two-level MRTs detecting main effects
power.2

Budget and/or sample size, power, MDES calculation for two-level CRTs detecting main effects
odr-package

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

Relative precision and efficiency (RPE) calculation
re

Relative efficiency (RE) calculation
power.3m

Budget and/or sample size, power, MDES calculation for three-level MRTs detecting main effects
power.4

Budget and/or sample size, power, MDES calculation for four-level CRTs detecting main effects
power.4m

Budget and/or sample size, power, MDES calculation for four-level MRTs detecting main effects
power.1

Budget and/or sample size, power, MDES calculation for single-level experiments detecting main effects