dep.t.test.second: A t-test with dependent samples using published work:...

In rpsychi: Statistics for psychiatric research

Description

dep.t.test.second conducts a t-test with dependent samples using published work.

Usage

    dep.t.test.second(m, sd, n, corr, 
            unbiased = TRUE, sig.level = 0.05, digits = 3)

Arguments

m	a numeric vector contains the means (length(m) = 2)
sd	a numeric vector contains the sample/unbiased standard deviations (length(sd) = 2)
n	a numeric contains the sample size (length(n) = 2)
corr	a numeric contains the correlation
unbiased	sd contains unbiased standard deviations (unbiased = TRUE, default) or sample standard deviations (unbiased = FALSE)
sig.level	a numeric contains the significance level (default 0.05)
digits	the specified number of decimal places (default 3)

Details

This function conducts a t-test with dependent samples using published work.

Value

The returned object of dep.t.test.second contains the following components:

samp.stat	returns the means, standard deviations, sample size, and correlation
raw.difference	returns a raw mean difference, its' confidence interval, and standard error
standardized.difference	returns a standardized mean difference (Hedges's g) and its' approximate confidence interval for a population standardized mean difference

Author(s)

Yasuyuki Okumura
Department of Social Psychiatry,
National Institute of Mental Health,
National Center of Neurology and Psychiatry
[e-mail]

References

Kline RB (2004) Beyond significance testing: Reforming data analysis methods in behavioral research. Washington: American Psychological Association.

See Also

dep.t.test

Examples

 
##Kline (2004) Table 4.4
dat <- data.frame(y = c(9,12,13,15,16,8,12,11,10,14),
                  x =  rep(factor(c("a","b")), each=5),
                  subj = rep(paste("s", 1:5, sep=""), times=2)
                  )
datwide <- reshape(dat, direction="wide", idvar="subj", timevar="x")

dep.t.test.second(m = tapply(dat$y, dat$x, mean),
                  sd = tapply(dat$y, dat$x, sd),
                  n = nlevels(dat$subj),
                  corr = cor(datwide[,2:3])[1,2]
                  )

dep.t.test.second(m = tapply(dat$y, dat$x, mean),
                  sd = tapply(dat$y, dat$x, sd),
                  n = 30,
                  corr = cor(datwide[,2:3])[1,2]
                  )

rpsychi documentation built on May 1, 2019, 10:10 p.m.