Friedman test for non-parametric analysis of repeated measures data with continuous or ordinal outcomes. This is the non-parametric alternative to repeated measures ANOVA when normality assumptions are violated. It tests whether the median values differ significantly across multiple related measurements or time points.
Usage
friedmantest(
data,
dependent,
subject,
within,
method = "asymptotic",
alpha = 0.05,
posthoc = TRUE,
posthoc_method = "nemenyi",
correction = "bonferroni",
effect_size = TRUE,
confidence_level = 0.95,
show_ranks = TRUE,
show_descriptives = TRUE,
show_assumptions = TRUE,
clinical_interpretation = TRUE
)Arguments
- data
the data as a data frame
- dependent
Continuous or ordinal dependent variable measured repeatedly
- subject
Variable identifying subjects/cases for repeated measurements
- within
Factor variable indicating the repeated measure conditions/time points
- method
Method for calculating p-values
- alpha
Alpha level for hypothesis testing
- posthoc
Perform pairwise post-hoc comparisons when Friedman test is significant
- posthoc_method
Method for post-hoc pairwise comparisons
- correction
Multiple comparison correction method for post-hoc tests
- effect_size
Include effect size measures (Kendall's W coefficient of concordance)
- confidence_level
Confidence level for confidence intervals
- show_ranks
Show detailed rank analysis and mean rank comparisons
- show_descriptives
Show descriptive statistics for each condition
- show_assumptions
Assess assumptions and provide recommendations
- clinical_interpretation
Provide clinical interpretation guidance for results
Value
A results object containing:
results$instructions | a html | ||||
results$dataInfo | a table | ||||
results$descriptiveStats | a table | ||||
results$friedmanTest | a table | ||||
results$effectSize | a table | ||||
results$rankAnalysis | a table | ||||
results$pairwiseComparisons | a table | ||||
results$assumptionAssessment | a table | ||||
results$clinicalInterpretation | a table | ||||
results$boxplotByCondition | an image | ||||
results$meanRankPlot | an image | ||||
results$pairwiseComparisonPlot | an image | ||||
results$profilePlot | an image | ||||
results$methodExplanation | a html |
Tables can be converted to data frames with asDF or as.data.frame. For example:
results$dataInfo$asDF
as.data.frame(results$dataInfo)