| findWidthCRDDiff {MBESS} | R Documentation |
Find the width of CI of unstandardized condition means difference. Users may use the model with or without covariates. See further details at Pornprasertmanit and Schneider (2010, submitted).
findWidthCRDDiff(nclus, nindiv, prtreat, tauy=NULL, sigma2y=NULL, totalvar=NULL, iccy=NULL, r2between = 0, r2within = 0, numpredictor = 0, assurance=NULL, conflevel = 0.95)
nclus |
The desired number of clusters |
nindiv |
The number of individuals in each cluster (cluster size) |
prtreat |
The proportion of treatment clusters |
tauy |
The residual variance in the between level before accounting for the covariates |
sigma2y |
The residual varaince in the within level before accounting for the covariate |
totalvar |
The total resiudal variance before accounting for the covariate |
iccy |
The intraclass correlation of the dependent variable |
r2within |
The proportion of variance explained in the within level (used when |
r2between |
The proportion of variance explained in the between level (used when |
numpredictor |
The number of predictors used in the between level |
assurance |
The degree of assurance, which is the value with which confidence can be placed that describes the likelihood of obtaining a confidence interval less than the value specified (e.g, .80, .90, .95) |
conflevel |
The desired level of confidence for the confidence interval |
The width of CI of unstandardized condition means difference. If assurance = NULL, the value represents the expected width. If assurance is specified as a number, the width value will have the proprotion of the specified assurance that the the likelihood of obtaining a confidence interval less than the outcome width
Sunthud Pornprasertmanit (University of Kansas; psunthud@ku.edu)
Pornprasertmanit, S., & Schneider, W. J. (2010). Efficient sample size for power and desired accuracy in Cohen's d estimation in two-group cluster randomized design (Master Thesis). Illinois State University, Normal, IL.
Pornprasertmanit, S., & Schneider, W. J. (submitted). Accuracy in parameter estimation in two-condition cluster randomized design.
## Not run: findWidthCRDDiff(80, 10, 0.25, tauy=0.25, sigma2y=0.75) ## End(Not run)