jmv (version 2.5.6)

ttestPS: Paired Samples T-Test

Description

The Student's paired samples t-test (sometimes called a dependent-samples t-test) is used to test the null hypothesis that the difference between pairs of measurements is equal to zero. A low p-value suggests that the null hypothesis is not true, and that the difference between the measurement pairs is not zero.

Usage

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

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)

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; measure 1 different to measure 2, measure 1 greater than measure 2, and measure 2 greater than measure 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

ci

TRUE or FALSE (default), provide confidence intervals

ciWidth

a number between 50 and 99.9 (default: 95), the width of confidence intervals

effectSize

TRUE or FALSE (default), provide effect sizes

ciES

TRUE or FALSE (default), provide confidence intervals for the effect-sizes

ciWidthES

a number between 50 and 99.9 (default: 95), the width of confidence intervals for the effect sizes

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

Details

The Student's paired samples t-test assumes that pair differences follow a normal distribution -- in the case that one is unwilling to assume this, the non-parametric Wilcoxon signed-rank can be used in it's place (However, note that the Wilcoxon signed-rank has a slightly different null hypothesis; that the two groups of measurements follow the same distribution).

Examples

# \donttest{
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
#  --------------------------------------------------------------
#
# }