R: Compute the P value that the observed and expected tables...

ptw2011.gof.test {rpf} | R Documentation

## Compute the P value that the observed and expected tables come from the same distribution

### Description

This test is an alternative to Pearson's X^2 goodness-of-fit test. In contrast to Pearson's X^2, no ad hoc cell collapsing is needed to avoid an inflated false positive rate in situations of sparse cell frequences. The statistic rapidly converges to the Monte-Carlo estimate as the number of draws increases.

### Usage

    ptw2011.gof.test(observed, expected)

### Arguments

`observed` | observed matrix
`expected` | expected matrix

### Value

The P value indicating whether the two tables come from the same distribution. For example, a significant result (P < alpha level) rejects the hypothesis that the two matrices are from the same distribution.

### References

Perkins, W., Tygert, M., & Ward, R. (2011). Computing the confidence levels for a root-mean-square test of goodness-of-fit. Applied Mathematics and Computations, 217(22), 9072-9084.

### Examples

    draws <- 17
    observed <- matrix(c(.294, .176, .118, .411), nrow=2) * draws
    expected <- matrix(c(.235, .235, .176, .353), nrow=2) * draws
    ptw2011.gof.test(observed, expected)  # not signficiant

[Package rpf version 0.59 Index]