dep.oneway: A one-way design with dependent samples using individual...
In rpsychi: Statistics for psychiatric research

Description Usage Arguments Details Value Author(s) References See Also Examples

dep.oneway conducts a one-way design with dependent samples, namely one-way repeated-measures analysis of variance, using individual data.

1 2	dep.oneway(formula, data, block, contr = NULL, sig.level = 0.05, digits = 3)

`formula`	two-sided formula; the left-hand-side of which gives one dependent variable containing a numeric variable, and the right-hand-side of one independent variable containing a factor with two or more levels
`data`	a data frame contains the variables in the `fomrmula` and `block`
`block`	a character string specify the blocking variable
`contr`	a matrix or vector contains the contrast weights
`sig.level`	a numeric contains the significance level (default 0.05)
`digits`	the specified number of decimal places (default 3)

This function conducts a one-way design with dependent samples, namely one-way repeated-measures analysis of variance, using individual data. If you do not specify contr, all possible pairwise contrasts will be calculated.

The returned object of dep.oneway contains the following components:

`anova.table`	returns a ANOVA table containing sums of squares, degrees of freedom, mean squares, F values, and a p value
`omnibus.es`	returns a omnibus effect size which is a partial η^2
`raw.contrasts`	returns raw mean differences, their confidence intervals, and standard errors
`standardized.contrasts`	returns standardized mean differences for the contrasts (Hedges's g) and their approximate confidence intervals for population standardized mean differences

Yasuyuki Okumura
Department of Social Psychiatry,
National Institute of Mental Health,
National Center of Neurology and Psychiatry
yokumura@blue.zero.jp

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

dep.oneway.second

##Kline (2004) Table 6.3
dat <- data.frame(y = c(9,12,13,15,16,
                       8,12,11,10,14,
                       10,11,13,11,15),
                  x =  rep(factor(c("a","b","c")), each=5),
                  subj = rep(paste("s", 1:5, sep=""), times=3)
                  )
dep.oneway(formula = y~x, data=dat, block="subj")


##contrast 1: a - c, contrast 2 : 1/2(a + c) - b
my.cont <- matrix(c(1,0,-1,1/2,-1,1/2), ncol=3, nrow=2, byrow=TRUE)
dep.oneway(formula = y~x, data=dat, block="subj", contr=my.cont)