# dprime_compare: Test the 'any-differences' hypothesis and estimate common... In sensR: Thurstonian Models for Sensory Discrimination

## Description

This function will test the 'any-differences' hypothesis (conceptually a one-way ANOVA test for d-primes) with one of the Wald, Pearson or likelihood ratio chi-square test statistics. The common d-prime is estimated with ML or weighted average.

## Usage

 ```1 2 3``` ```dprime_compare(correct, total, protocol, conf.level = 0.95, statistic = c("likelihood", "Pearson", "Wald.p", "Wald.d"), estim = c("ML", "weighted.avg")) ```

## Arguments

 `correct` a numeric vector of the number of correct answers; one element for each test. `total` a numeric vector of the total number of trials; one element for each test. `protocol` a character vector or factor naming the protocol used; one element for each test. Currently the following protocols are supported: `"triangle", "duotrio", "threeAFC", "twoAFC", "tetrad"`. `conf.level` the confidence level for the estimated common d-prime. `statistic` the test statistic for testing the 'any-differences' hypothesis. `estim` The estimation method for the common d-prime.

## Details

The vectors `correct`, `total` and `protocol` have to be of the same length.

The function has a print method.

## Value

an object of class `"dprime_compare"` with the following elements

 `stat.value` the value of the (chi-square) test statistic for the 'any-differences' hypothesis. `df` the degrees of freedom for the `stat.value` test statistic. `p.value` the p-value for the 'any-differences' test. `statistic` the name of the test statistic for the 'any-differences' test. `data` the data table produced by `dprime_table`. `coefficients` 'table' with estimated common d-prime, standard error and confidence limits storred as a one-row `data.frame`. `conf.level` confidence level for the common d-prime. `conf.int` the confidence interval for the common d-prime. `estim` the estimation method for the common d-prime. `conf.method` the statistical method/test statistic used to compute the confidence interval for the common d-prime.

## Author(s)

Rune Haubo B Christensen

`dprime_test`, `dprime_table`, `posthoc.dprime_compare`.
 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15``` ```## 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)) ## Other estimation/statistic options: dprime_compare(x, n, protocol, estim="weighted.avg") dprime_compare(x, n, protocol, statistic="Pearson") dprime_compare(x, n, protocol, statistic="Wald.p") dprime_compare(x, n, protocol, statistic="Wald.d") ```