chisqPostHoc {NCStats} R Documentation

## Tests for significant differences among all pairs of populations in a chi-square test.

### Description

Tests for significant differences among all pairs of populations in a chi-square test.

### Usage

```chisqPostHoc(chi, popsInRows = TRUE, control = stats::p.adjust.methods,
digits = 4, verbose = TRUE)
```

### Arguments

 `chi` A `chisq.test` object `popsInRows` A logical indicating whether the populations form the rows (default; `=TRUE`) of the table or not (`=FALSE`) `control` A string indicating the method of control to use (see details) `digits` A numeric that controls the number of digits to print `verbose` A logical that conrols whether the warning message from the individual `chisq.test` calls are printed `...` Other arguments sent to `print`

### Details

Post-hoc tests for which pairs of populations differ following a significant chi-square test can be constructed by performing all chi-square tests for all pairs of populations and then adjusting the resulting p-values for inflation due to multiple comparisons. The adjusted p-values can be computed with a wide variety of methods (see `p.adjust.methods`). This function basically works as a wrapper function that sends the unadjusted “raw” p-values from each pair-wise chi-square test to the `p.adjust` function in the base R program. The `p.adjust` function should be consulted for further description of the methods used.

### Value

A data.frame with a description of the pairwise comparisons, the raw p-values, and the adjusted p-values.

`chisq.test` and `p.adjust`.

### Examples

```# Makes a table of observations -- similar to first example in chisq.test
M <- as.table(rbind(c(76, 32, 46), c(48,23,47), c(45,34,78)))
dimnames(M) <- list(sex=c("Male","Female","Juv"),loc=c("Lower","Middle","Upper"))
M
# Fits chi-square test and shows summary
( chi1 <- chisq.test(M) )
# Shows post-hoc pairwise comparisons using fdr method
chisqPostHoc(chi1)

# Transpose the observed table to demonstrate use of popsInRows=FALSE
( chi2 <- chisq.test(t(M)) )
chisqPostHoc(chi2,popsInRows=FALSE)

# How does it handle spares columns
( obs <- matrix(c(20,0,20,30,20,20,10,0,0),nrow=3,byrow=TRUE) )
chi1 <- chisq.test(obs)
chisqPostHoc(chi1)
( obs <- matrix(c(20,0,0,30,20,20,10,0,0),nrow=3,byrow=TRUE) )
chi1 <- chisq.test(obs)
chisqPostHoc(chi1)

```

[Package NCStats version 0.4.7 Index]