samplesize

Help for package samplesize const macros = { "\\R": "\\textsf{R}", "\\mbox": "\\text", "\\code": "\\texttt"}; function processMathHTML() { var l = document.getElementsByClassName('reqn'); for (let e of l) { katex.render(e.textContent, e, { throwOnError: false, macros }); } return; } Package {samplesize} Contents samplesize-package n.ttest n.wilcox.ord Type: Package Title: Sample Size Calculation for Various t-Tests and Wilcoxon-Test Version: 0.2-4 Date: 2016-12-22 Author: Ralph Scherer Maintainer: Ralph Scherer <shearer.ra76@gmail.com> Description: Computes sample size for Student's t-test and for the Wilcoxon-Mann-Whitney test for categorical data. The t-test function allows paired and unpaired (balanced / unbalanced) designs as well as homogeneous and heterogeneous variances. The Wilcoxon function allows for ties. License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] URL: https://github.com/shearer/samplesize BugReports: https://github.com/shearer/samplesize/issues NeedsCompilation: no Packaged: 2016-12-23 21:02:40 UTC; ralph Repository: CRAN Date/Publication: 2016-12-24 11:24:04 Computes sample size for several two-sample tests Description Computes sample size for independent and paired Student's t-test, Student's t-test with Welch-approximation, Wilcoxon-Mann-Whitney test with and without ties on ordinal data Details Package: samplesize Type: Package Version: 0.2-4 Date: 2016-12-22 License: GPL (>=2) LazyLoad: yes n.ttest(): sample size for Student's t-test and t-test with Welch approximation n.wilcox.ord(): sample size for Wilcoxon-Mann-Whitney test with and without ties Author(s) Ralph Scherer Maintainer: Ralph Scherer <shearer.ra@gmail.com> References Bock J., Bestimmung des Stichprobenumfangs fuer biologische Experimente und kontrollierte klinische Studien. Oldenbourg 1998 Zhao YD, Rahardja D, Qu Yongming. Sample size calculation for the Wilcoxon-Mann-Whitney test adjusting for ties. Statistics in Medicine 2008; 27:462-468 n.ttest computes sample size for paired and unpaired t-tests. Description n.ttest computes sample size for paired and unpaired t-tests. Design may be balanced or unbalanced. Homogeneous and heterogeneous variances are allowed. Usage n.ttest(power = 0.8, alpha = 0.05, mean.diff = 0.8, sd1 = 0.83, sd2 = sd1, k = 1, design = "unpaired", fraction = "balanced", variance = "equal") Arguments power Power (1 - Type-II-error) alpha Two-sided Type-I-error mean.diff Expected mean difference sd1 Standard deviation in group 1 sd2 Standard deviation in group 2 k Sample fraction k design Type of design. May be paired or unpaired fraction Type of fraction. May be balanced or unbalanced variance Type of variance. May be homo- or heterogeneous Value Total sample size Sample size for both groups together Sample size group 1 Sample size in group 1 Sample size group 2 Sample size in group 2 Author(s) Ralph Scherer References Bock J., Bestimmung des Stichprobenumfangs fuer biologische Experimente und kontrollierte klinische Studien. Oldenbourg 1998 Examples n.ttest(power = 0.8, alpha = 0.05, mean.diff = 0.80, sd1 = 0.83, k = 1, design = "unpaired", fraction = "balanced", variance = "equal") n.ttest(power = 0.8, alpha = 0.05, mean.diff = 0.80, sd1 = 0.83, sd2 = 2.65, k = 0.7, design = "unpaired", fraction = "unbalanced", variance = "unequal") Sample size for Wilcoxon-Mann-Whitney for ordinal data Description Function computes sample size for the two-sided Wilcoxon test when applied to two independent samples with ordered categorical responses. Usage n.wilcox.ord(power = 0.8, alpha = 0.05, t, p, q) Arguments power required Power alpha required two-sided Type-I-error level t sample size fraction n/N, where n is sample size of group B and N is the total sample size p vector of expected proportions of the categories in group A, should sum to 1 q vector of expected proportions of the categories in group B, should be of equal length as p and should sum to 1 Details This function approximates the total sample size, N, needed for the two-sided Wilcoxon test when comparing two independent samples, A and B, when data are ordered categorical according to Equation 12 in Zhao et al.(2008). Assuming that the response consists of D ordered categories C_1 ,..., C_D . The expected proportions of these categories in two treatments A and B must be specified as numeric vectors p_1,...,p_D and q_1,...,q_D , respectively. The argument t allows to compute power for an unbalanced design, where t=n_B/N is the proportion of sample size in treatment B. Value total sample size Total sample size m Sample size group 1 n Sample size group 2 Author(s) Ralph Scherer References Zhao YD, Rahardja D, Qu Yongming. Sample size calculation for the Wilcoxon-Mann-Whitney test adjsuting for ties. Statistics in Medicine 2008; 27:462-468 Examples ## example out of: ## Zhao YD, Rahardja D, Qu Yongming. ## Sample size calculation for the Wilcoxon-Mann-Whitney test adjsuting for ties. ## Statistics in Medicine 2008; 27:462-468 n.wilcox.ord(power = 0.8, alpha = 0.05, t = 0.53, p = c(0.66, 0.15, 0.19), q = c(0.61, 0.23, 0.16))