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

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About

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. doi:10.3102/1076998620912418. (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. doi:10.1080/19345747.2021.1953200. (3) Shen, Z., & Kelcey, B. (2022a). Optimal sample allocation in multisite randomized trials. The Journal of Experimental Education. doi:10.1080/00220973.2020.1830361. (4) Champely, S. (2020). pwr: Basic functions for power analysis (Version 1.3-0) [Software]. Available from .

Key Metrics

Version 1.4.4
R ≥ 3.3.0
Published 2023-08-08 405 days ago
Needs compilation? no
License GPL-3
CRAN checks odr results
Language en-US

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Maintainer

Maintainer

Zuchao Shen

Authors

Zuchao Shen

aut / cre

Benjamin Kelcey

aut

Material

Reference manual
Package source

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ExperimentalDesign

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Package 'odr'

macOS

r-release

arm64

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arm64

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x86_64

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x86_64

Windows

r-devel

x86_64

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x86_64

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Old Sources

odr archive

Depends

R ≥ 3.3.0
stats ≥ 3.0.0
graphics ≥ 3.0.0
base ≥3.0.0

Suggests

rmarkdown
knitr
markdown