Wide format version of the longitudinal_data dataset with one row per subject and separate columns for each time point. Useful for certain repeated measures analyses and data visualization.
Format
A data frame with 120 rows and 8 variables:
- subject_id
Subject identifier (factor, 1-120)
- group
Treatment group (Control, Treatment)
- age
Age in years (numeric)
- gender
Gender (Male, Female)
- score_T1
Outcome score at Time 1
- score_T2
Outcome score at Time 2
- score_T3
Outcome score at Time 3
- score_T4
Outcome score at Time 4
Details
This is the wide format version of longitudinal_data with
outcome scores spread across columns by time point. Missing values
represent subject dropout or missed assessments.
See also
longitudinal_data for the long format version
Examples
# Load required packages and data
library(dplyr)
data(longitudinal_data_wide)
# Change over the four time points
friedman_test(longitudinal_data_wide, score_T1, score_T2, score_T3, score_T4)
#> Friedman Test: score_T1, score_T2, score_T3, score_T4
#> chi2(3) = 61.192, p < 0.001 ***, Kendall's W = 0.272 (weak), N = 75
#> Use summary() for detailed output.
# Change between two time points
wilcoxon_test(longitudinal_data_wide, score_T1, score_T2)
#> Wilcoxon Signed-Rank Test: score_T2 - score_T1
#> Z = -5.427, p < 0.001 ***, r = 0.530 (large), N = 105
#> Use summary() for detailed output.