Package: odr 1.4.4

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

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 <https://CRAN.R-project.org/package=pwr>.

Authors:Zuchao Shen [aut, cre], Benjamin Kelcey [aut]

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# Install 'odr' in R:
install.packages('odr', repos = c('https://zuchaoshen.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/zuchaoshen/odr/issues

On CRAN:

23 exports 0.63 score 0 dependencies 19 scripts 255 downloads

Last updated 1 years agofrom:f23fc67c4f. Checks:OK: 7. Indexed: yes.

TargetResultDate
Doc / VignettesOKSep 01 2024
R-4.5-winOKSep 01 2024
R-4.5-linuxOKSep 01 2024
R-4.4-winOKSep 01 2024
R-4.4-macOKSep 01 2024
R-4.3-winOKSep 01 2024
R-4.3-macOKSep 01 2024

Exports:gen.design.parsod.1od.1.111od.2od.2.221od.2mod.2m.111od.3od.3mod.4od.4mpower.1power.1.111power.2power.2.221power.2mpower.2m.111power.3power.3mpower.4power.4mrerpe

Dependencies:

Package 'odr'

Rendered fromodr.Rmdusingknitr::rmarkdownon Sep 01 2024.

Last update: 2023-08-08
Started: 2021-08-29

Readme and manuals

Help Manual

Help pageTopics
Optimal Design and Statistical Power for Experimental Studies Investigating Main, Mediation, and Moderation Effectsodr-package odr
Generate optimal design parameters using ant colony optimizationgen.design.pars
Optimal sample allocation calculation for single-level experiments detecting main effectsod.1
Optimal sample allocation calculation for single-level randomized controlled trials (RCTs) investigating mediation effects (1-1-1)od.1.111
Optimal sample allocation calculation for two-level CRTs detecting main effectsod.2
Optimal sample allocation calculation for two-level CRTs probing mediation effects with cluster-level mediatorsod.2.221
Optimal sample allocation calculation for two-level MRTs detecting main effectsod.2m
Optimal sample allocation calculation for two-level multisite-randomized trials investigating mediation effects with individual-level mediators (1-1-1)od.2m.111
Optimal sample allocation calculation for three-level CRTs detecting main effectsod.3
Optimal sample allocation calculation for three-level MRTs detecting main effectsod.3m
Optimal sample allocation calculation for four-level CRTs detecting main effectsod.4
Optimal sample allocation calculation for four-level MRTs detecting main effectsod.4m
Budget and/or sample size, power, MDES calculation for single-level experiments detecting main effectspower.1
Budget and/or sample size, power, MDES calculation for MRTs investigating mediation effects with individual-level mediatorspower.1.111
Budget and/or sample size, power, MDES calculation for two-level CRTs detecting main effectspower.2
Budget and/or sample size, power calculation for CRTs probing mediation effects with cluster-level mediatorspower.2.221
Budget and/or sample size, power, MDES calculation for two-level MRTs detecting main effectspower.2m
Budget and/or sample size, power, MDES calculation for MRTs investigating mediation effects with individual-level mediatorspower.2m.111
Budget and/or sample size, power, MDES calculation for three-level CRTs detecting main effectspower.3
Budget and/or sample size, power, MDES calculation for three-level MRTs detecting main effectspower.3m
Budget and/or sample size, power, MDES calculation for four-level CRTs detecting main effectspower.4
Budget and/or sample size, power, MDES calculation for four-level MRTs detecting main effectspower.4m
Relative efficiency (RE) calculationre
Relative precision and efficiency (RPE) calculationrpe