Package: PowerUpR
Type: Package
Title: Power Analysis Tools for Multilevel Randomized Experiments
Version: 1.1.0
Date: 2021-10-24
Authors@R: c(
    person("Metin", "Bulus", email = "bulusmetin@gmail.com", role = c("aut", "cre")),
    person("Nianbo", "Dong", role = "aut"),
    person("Benjamin", "Kelcey", role = "aut"),
    person("Jessaca", "Spybrook", role = "aut")
    )
Description: 
 Includes tools to calculate statistical power, minimum detectable effect size (MDES), MDES difference (MDESD), and minimum required sample size for various multilevel randomized experiments (MRE) with continuous outcomes.
 Accomodates 14 types of MRE designs to detect main treatment effect, seven types of MRE designs to detect moderated treatment effect (2-1-1, 2-1-2, 2-2-1, 2-2-2, 3-3-1, 3-3-2, and 3-3-3 designs; <total.lev> - <trt.lev> - <mod.lev>),
 five types of MRE designs to detect mediated treatment effects (2-1-1, 2-2-1, 3-1-1, 3-2-1, and 3-3-1 designs; <trt.lev> - <med.lev> - <out.lev>), four types of partially nested (PN) design to detect main treatment effect,
 and three types of PN designs to detect mediated treatment effects (2/1, 3/1, 3/2; <trt.arm.lev> / <ctrl.arm.lev>). 
 See 'PowerUp!' Excel series at <https://www.causalevaluation.org/>. 
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
License: GPL (>= 3)
NeedsCompilation: no
Author: Metin Bulus [aut, cre],
  Nianbo Dong [aut],
  Benjamin Kelcey [aut],
  Jessaca Spybrook [aut]
Maintainer: Metin Bulus <bulusmetin@gmail.com>
Packaged: 2021-10-25 12:22:47 UTC; LENOVO
Repository: CRAN
Date/Publication: 2021-10-25 16:10:02 UTC
Built: R 4.3.3; ; 2025-01-24 11:11:18 UTC; unix
