Description Usage Arguments Details Value Author(s) See Also Examples

This function provides estimates and p-values for post-hoc tests such as pairwise comparisons. p-values are (by default) adjusted for multiplicity.

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 | ```
posthoc(x, ...)
## S3 method for class 'dprime_compare'
posthoc(x, alpha = 0.05,
test = c("pairwise", "common", "base", "zero"), base = 1,
alternative = c("two.sided", "less", "greater"),
statistic = c("likelihood", "Wald"),
padj.method = c("holm", "bonferroni", "none"), ...)
## S3 method for class 'dprime_test'
posthoc(x, alpha = 0.05,
test = c("pairwise", "common", "base", "zero"), base = 1,
alternative = c("two.sided", "less", "greater"),
statistic = c("likelihood", "Wald"),
padj.method = c("holm", "bonferroni", "none"), ...)
``` |

`x` |
an object of class |

`alpha` |
the significance level for tests and confidence intervals. |

`test` |
the type of post-hoc tests performed. Se the details section for further details. |

`base` |
when |

`alternative` |
direction of the hypothesis test. |

`statistic` |
The test statistic used - currently there is only partial support
for |

`padj.method` |
controls the method by which p-values are adjusted for
multiplicity. Any one of the values in |

`...` |
currently not used. |

The `test`

argument specifies the type of test
performed. `"pairwise"`

performs all pairwise comparisons and
produces a compact letter display indicating groups of experiments
that different/not-different. `"common"`

tests, for each
experiment in turn, if the by-experiment d-prime is different from
a common d-prime computed from the remaining
experiments. `"base"`

provides pairwise comparisons to a
single experiment indicated by the separate argument `base`

. If
`test = "zero"`

all d-primes are tested versus zero. As a final
option a numeric value can be supplied, e.g. `test = 1`

in
which case all d-primes are tested versus one. Note that
`test = 0`

gives the same test as `test = "zero"`

.

When `test = "pairwise"`

a compact letter display is provided and
it is determined from the p-values *after* adjustment of these for
multiplicity.

The `dprime_compare`

and `dprime_test`

methods a have
(common) print method.

an object of class `c(paste0("posthoc.", class(x)), class(x))`

with the following elements from the original object, `x`

and :

`posthoc` |
coefficient table for the post-hoc tests. |

`test` |
the value of the |

`alternative` |
the value of the |

`padj.method` |
the method used to adjust p-values with. |

`base` |
the value of the |

`posthoc.stat` |
name of the statistic for the post-hoc tests. |

`Letters` |
if |

`dprime0` |
unless |

Rune Haubo B Christensen

`dprime_test`

, `dprime_table`

,
`dprime_compare`

.

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 | ```
## Make some fake data:
n <- rep(40, 4)
x <- c(25, 25, 30, 35)
protocol <- c("triangle", "duotrio", "threeAFC", "twoAFC")
## Look at the data table with d-primes etc.:
dprime_table(x, n, protocol)
## 'any differences' test:
## ML estimation and test with likelihood statistic:
(dpc <- dprime_compare(x, n, protocol))
posthoc(dpc, alpha=.1) ## test="pairwise"
## Test if each d' is different from the common d' estimated from the
## remaining experiments:
posthoc(dpc, test="common")
## Test if d' from experiment 2 is different from the others (with
## adjustment for multiplicity):
posthoc(dpc, test="base", base=2)
## Test if each d' is different from 2 (with Bonferroni adjustment for
## multiplicity) using the Wald statistic:
posthoc(dpc, test=2, stat="Wald", padj.method="bonferroni")
``` |

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