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, qq = 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
`qq`	`TRUE` or `FALSE` (default), provide a Q-Q plot of residuals
`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 0.9.2.0 Index]