lsr (version 0.5.2)

goodnessOfFitTest: Chi-square test against specified probabilities

Description

Convenience function that runs a chi-square goodness of fit test against specified probabilities. This is a wrapper function intended to be used for pedagogical purposes only.

Usage

goodnessOfFitTest(x, p = NULL)

Arguments

x

Factor variable containing the raw outcomes.

p

Numeric variable containing the null-hypothesis probabilities (default = all outcomes equally likely)

Value

An object of class 'gofTest'. When printed, the output is organised into four short sections. The first section lists the name of the test and the variables included. The second lists the null and alternative hypotheses for the test. The third shows the observed frequency table, the expected frequency table under the null hypothesis, and the probabilities specified by the null. The fourth prints out the test results.

Details

The goodnessOfFitTest function runs the chi-square goodness of fit test of the hypothesis that the outcomes in the factor x were generated according to the probabilities in the vector p. The probability vector p must be a numeric variable of length nlevels(x). If no probabilities are specified, all outcomes are assumed to be equally likely.

See Also

chisq.test, associationTest, cramersV

Examples

# NOT RUN {
# raw data
gender <- factor(
  c( "male","male","male","male","female","female",
     "female","male","male","male" ))

# goodness of fit test against the hypothesis that males and
# females occur with equal frequency
goodnessOfFitTest( gender )

# goodness of fit test against the hypothesis that males appear
# with probability .6 and females with probability .4.
goodnessOfFitTest( gender, p=c(.4,.6) )
goodnessOfFitTest( gender, p=c(female=.4,male=.6) )
goodnessOfFitTest( gender, p=c(male=.6,female=.4) )

# }