R: Paired Samples T-Test

ttestPS {jmv} | R Documentation

## Paired Samples T-Test

### Description

Paired Samples T-Test

### Usage

    ttestPS(data, pairs, students = TRUE, bf = FALSE, bfPrior = 0.707,
      wilcoxon = FALSE, hypothesis = "different", norm = FALSE,
      meanDiff = FALSE, effectSize = FALSE, ci = FALSE, ciWidth = 95,
      desc = FALSE, plots = FALSE, miss = "perAnalysis")

### Arguments

`data` | the data as a data frame
`pairs` | a list of lists specifying the pairs of measurement in `data`
`students` | `TRUE` (default) or `FALSE`, perform Student's t-tests
`bf` | `TRUE` or `FALSE` (default), provide Bayes factors
`bfPrior` | a number between 0.5 and 2 (default 0.707), the prior width to use in calculating Bayes factors
`wilcoxon` | `TRUE` or `FALSE` (default), perform Wilcoxon signed rank tests
`hypothesis` | `'different'` (default), `'oneGreater'` or `'twoGreater'`, the alternative hypothesis; group 1 different to group 2, group 1 greater than group 2, and group 2 greater than group 1 respectively
`norm` | `TRUE` or `FALSE` (default), perform Shapiro-wilk normality tests
`meanDiff` | `TRUE` or `FALSE` (default), provide means and standard errors
`effectSize` | `TRUE` or `FALSE` (default), provide effect sizes
`ci` | `TRUE` or `FALSE` (default), provide confidence intervals
`ciWidth` | a number between 50 and 99.9 (default: 95), the width of confidence intervals
`desc` | `TRUE` or `FALSE` (default), provide descriptive statistics
`plots` | `TRUE` or `FALSE` (default), provide descriptive plots
`miss` | `'perAnalysis'` or `'listwise'`, how to handle missing values; `'perAnalysis'` excludes missing values for individual dependent variables, `'listwise'` excludes a row from all analyses if one of its entries is missing.

### Value

A results object containing:

`results$ttest` |  |  |  |  | a table containing the t-test results
`results$norm` |  |  |  |  | a table containing the normality test results
`results$desc` |  |  |  |  | a table containing the descriptives
`results$plots` |  |  |  |  | an array of the descriptive plots

Tables can be converted to data frames with `asDF` or `as.data.frame`. For example:

`results$ttest$asDF`

`as.data.frame(results$ttest)`

### Examples

    ## Not run:
    data('bugs', package = 'jmv')

    ttestPS(bugs, pairs = list(
            list(i1 = 'LDLF', i2 = 'LDHF')))

    #
    #  PAIRED SAMPLES T-TEST
    #
    #  Paired Samples T-Test
    #  --------------------------------------------------------------
    #                                   statistic    df      p
    #  --------------------------------------------------------------
    #    LDLF    LDHF    Student's t        -6.65    90.0    < .001
    #  --------------------------------------------------------------
    #

    ## End(Not run)

[Package jmv version 0.8.6.2 Index]