Paired Samples T-Test

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.

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).

Example usage

data('bugs', package = 'jmv')

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

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


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


A results object containing:

results$ttest a table
results$norm a table
results$desc a table
results$plots an array of groups

Tables can be converted to data frames with asDF or For example:


Elements in arrays can be accessed with [[n]]. For example:

results$plots[[1]] # accesses the first element