pg-nonparametric

name	pg-nonparametric
description	Run or generate Pingouin code for rank-based non-parametric tests — Mann-Whitney U, Wilcoxon signed-rank, Kruskal-Wallis, Friedman, and Cochran Q — when outcomes are ordinal or parametric assumptions fail.

PG Nonparametric

Use when the outcome is ordinal, or continuous but non-normal with small n, so a rank-based test is safer than a t test or ANOVA.

Load

Read:

• ../../references/supervision-gates.md
• ../../references/pingouin-api-quickref.md
• ../../references/apa-output-template.md if writing results.

Decision Rules

• Two independent groups -> pg.mwu(x, y) (Mann-Whitney U).
• Same participants measured twice / paired -> pg.wilcoxon(x, y) (signed-rank).
• Three or more independent groups, one factor -> pg.kruskal(data, dv, between).
• Three or more repeated conditions, continuous/ordinal -> pg.friedman(data, dv, within, subject).
• Three or more repeated conditions, binary outcome -> pg.cochran(data, dv, within, subject).
• Follow a significant omnibus with pg.pairwise_tests(..., parametric=False, padjust="holm").

Required Inputs

• Outcome column and its scale (ordinal or non-normal continuous).
• Grouping (between) or condition (within) column.
• Subject ID for paired/repeated designs.
• Post hoc correction: default holm.
• Alternative hypothesis: default two-sided (mwu/wilcoxon only).

Code Patterns

Mann-Whitney U (independent):

x = df.loc[df["group"].eq("A"), "score"]
y = df.loc[df["group"].eq("B"), "score"]
res = pg.mwu(x, y, alternative="two-sided").round(3)
pg.print_table(res)

Wilcoxon signed-rank (paired):

res = pg.wilcoxon(df["pre"], df["post"], alternative="two-sided").round(3)
pg.print_table(res)

Kruskal-Wallis (k independent groups):

res = pg.kruskal(data=df, dv="score", between="group").round(3)
pg.print_table(res)

Friedman (k repeated conditions):

res = pg.friedman(data=df, dv="score", within="condition", subject="id").round(3)
pg.print_table(res)

Cochran Q (binary repeated):

res = pg.cochran(data=df, dv="passed", within="condition", subject="id").round(3)
pg.print_table(res)

Output Checks

mwu/wilcoxon return U_val/W_val, p_val, RBC (rank-biserial), CLES. kruskal returns H, ddof1, p_unc; friedman returns Kendall W, Q, p_unc; cochran returns Q, dof, p_unc. Report the effect size, not just p.

Guardrails

• mwu is unpaired only; wilcoxon is paired only — do not swap them.
• Kruskal/Friedman/Cochran are omnibus; always follow a significant result with corrected pairwise tests.
• Rank tests compare distributions/ranks, not means; word conclusions accordingly.
• Prefer parametric tests when their assumptions hold (more power).
• End result-bearing answers with one compact S0-S5 audit line.