Calculates the Chi-square approximation to the z-test and the binomial approximation to the z-test.

1 | ```
z_tests_cfa(observed, expected, ccor = FALSE, ntotal = sum(observed))
``` |

`observed` |
a vector giving the observed frequencies. |

`expected` |
a vector giving the expected frequencies. |

`ccor` |
either a logical (TRUE / FALSE) determining wether to apply a continuity correction or not. When set to |

`ntotal` |
optional a numeric giving the total number of observations. By default ntotal is calculated as |

An continuity correction can be applied to the binomial approximation – see argument `ccor`

.

a list with z an p-values.

No references in the moment

1 2 3 4 5 6 7 8 | ```
#######################################
# expected counts for LienertLSD data example.
designmatrix<-design_cfg_cfa(kat=c(2,2,2)) # generate an designmatrix (only main effects)
data(LienertLSD) # load example data
observed<-LienertLSD[,4] # extract observed counts
expected<-expected_cfa(des=designmatrix, observed=observed) # calculation of expected counts
z_tests_cfa(observed,expected)
#######################################
``` |

Questions? Problems? Suggestions? Tweet to @rdrrHQ or email at ian@mutexlabs.com.

Please suggest features or report bugs with the GitHub issue tracker.

All documentation is copyright its authors; we didn't write any of that.

Embedding an R snippet on your website

Add the following code to your website.

For more information on customizing the embed code, read Embedding Snippets.