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rpsychi (version 0.8)

Statistics for psychiatric research

Description

The rpsychi offers a number of functions for psychiatry, psychiatric nursing, clinical psychology. Functions are primarily for statistical significance testing using published work. For example, you can conduct a factorial analysis of variance (ANOVA), which requires only the mean, standard deviation, and sample size for each cell, rather than the individual data. This package covers fundamental statistical tests such as t-test, chi-square test, analysis of variance, and multiple regression analysis. With some exceptions, you can obtain effect size and its confidence interval. These functions help you to obtain effect size from published work, and then to conduct a priori power analysis or meta-analysis, even if a researcher do not report effect size in a published work.

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Version

Install

install.packages('rpsychi')

Monthly Downloads

23

Version

0.8

License

GPL (>= 2)

Maintainer

Yasuyuki Okumura

Last Published

January 3rd, 2012

Functions in rpsychi (0.8)

samplesize.r

Sample size estimation in the significance testing of a product moment correlation
ind.t.test

A t-test with independent samples using individual data: Reporting effect size
formatted

Convert a numeric vector into a character vector with the specified number of decimal place
dep.oneway.second

A one-way design with dependent samples using published work: Reporting effect size
r2cov

Convert correlation matrix into covariance matrix
ind.prop

A Z test for the equality of two proportions using individual data: Reporting effect size
dep.t.test

A t-test with dependent samples using individual data: Reporting effect size
ind.t.test.second

A t-test with independent samples using published work: Reporting effect size
ssd2sd

Convert sample standard deviation into unbiased one
dep.oneway

A one-way design with dependent samples using individual data: Reporting effect size
dep.t.test.second

A t-test with dependent samples using published work: Reporting effect size
power.r

Statistical power for the significance testing of a product moment correlation
samplesize.rsq

Sample size estimation in the F tests of variance proportions
power.multi

Statistical power for F tests of variance proportions
power.prop

Statistical power for differences between proportions
power.t

Statistical power for the t test for means
ind.oneway.second

A one-way design with independent samples using published work: Reporting effect size
power.f

Statistical power for F tests on means in the analysis of variance
FNONCT

Compute the noncentrality parameter of an F distribution
rpsychi-package

Statistics for psychiatric research
ind.oneway

A one-way design with independent samples using individual data: Reporting effect size
svar

Compute sample variance
samplesize.d

Sample size estimation in the t test for means
ind.prop.second

A Z test for the equality of two proportions using published workc
zero.r.test

A significance testing of a product moment correlation using individual data
sumfun

Compute summary statistics using library(doBy)
samplesize.h

Sample size estimation in the differences between proportions
md.pattern2

Display missing-data patterns
ssd

Compute sample standard deviation
zero.r.test.second

A significance testing of a product moment correlation using published work
ind.twoway

A two-way design with independent samples using individual data
multreg.second

A multiple regression analysis using published work
ind.twoway.second

A two-way design with independent samples using published work
lower2R

Convert a vector containing correlations into a correlation matrix
samplesize.etasq

Sample size estimation in the analysis of variance
power.f2

Statistical power for F tests on means in the two-way analysis of variance
multreg

A multiple regression analysis using individual data
groupSummary

Compute summary statistics by group