epiDisplay (version 3.5.0.2)

statStack: Statistics of a continuous variable stratified by factors

Description

Compares the difference in means or medians of the levels of a factor or list of factors

Usage

statStack (cont.var, by, dataFrame, iqr="auto", var.labels = TRUE, decimal = 1, 
    assumption.p.value = .01)

Arguments

cont.var

a single continuous variable in the data frame

by

a factor, or list of factors, each of length <code>nrow(dataFrame)</code>

iqr

to display median and inter-quartile range instead of mean and sd.

var.labels

use descriptions of the 'by' variables if available

dataFrame

source data frame of the variables

decimal

number of digits displayed after decimal point

assumption.p.value

level of Bartlett's test P value to judge whether the comparison and the test should be parametric

Value

an object of class 'statStack' and 'table'

Details

This function computes means/medians of a continuous variable in each level of the specified factor(s) and performs an appropriate statistical test.

The classes of the variable to compute statistics must be either 'integer' or 'numeric' why all 'by' variables must be 'factor'.

Like in 'tableStack', the argument 'iqr' has a default value being "auto". Non-parametric comparison and test will be automatically chosen if Bartlette's test P value is below the 'assumption.p.value'.Like in 'tableStack', the default value for the 'iqr' argument is "auto", which means non-parametric comparison and test will be automatically chosen if the P-value from Bartlett's test is below the value of the 'assumption.p.value' argument (0.01).

The user can force the function to perform a parametric test by setting 'iqr=NULL' and to perform a non-parametric test by setting 'iqr' to the name or index of the continuous variable.

By default, 'var.labels=TRUE' in order to give nice output.

See Also

'tableStack'

Examples

# NOT RUN {
statStack(Price, by=c(DriveTrain, Origin), dataFrame=Cars93)
statStack(Price, by=c(DriveTrain, Origin), dataFrame=Cars93, iqr=NULL)

Cars93$log10.Price <- log10(Cars93$Price)# added as the 28th variable
statStack(log10.Price, by=c(DriveTrain, Origin), dataFrame=Cars93)
statStack(log10.Price, by=c(DriveTrain, Origin), dataFrame=Cars93, iqr=28)
rm(Cars93)

data(Compaq)
statStack(year, by=c(hospital, stage:ses), dataFrame=Compaq)
# Note that var.labels 'Age group' is displayed instead of var. name 'agegr'
# }