One-shot planner for factor or cell comparisons, reporting m, FWER, suggested adjustments (Bonferroni/Sidak) and a post hoc recommendation (Holm, Tukey, Duncan, Gabriel, Scheffe, SNK, etc.) before testing.
Posthoc_planner(
model,
compare = NULL,
alpha = 0.05,
scope = c("factor", "cells"),
equal_var = TRUE,
unequal_n = FALSE,
independence = TRUE,
liberal_ok = FALSE,
orientation = c("rows", "cols"),
digits = 4,
percent_digits = 1,
observed_cells = TRUE
)data.frame. - orientation="rows": first column "Metric", rest columns are units (factor/cells). - orientation="cols": one row per unit, metrics as columns. Includes: g levels, m comparisons, global alpha, Bonferroni/Sidak alphas, FWERs (under independence), "Suggested p-value adjustment" and "Post hoc suggestion".
aov or lm object (complete model). Data are reconstructed with model.frame().
Character with the name(s) of the factor(s) to compare: - One name: main effect. - Several names: if scope="cells" compares A:B:... cells; if scope="factor", reports each factor. If omitted, uses all factors when scope="factor", or the first factor when scope="cells".
Overall significance level (FWER target), default 0.05.
"factor" compares each factor separately; "cells" compares interaction cells.
Logical; assume homoscedasticity (default TRUE).
Logical; expect moderate imbalance of group sizes (default FALSE).
Logical; if TRUE reports FWER "under independence" (default TRUE).
Logical; allows more liberal suggestions (LSD/Duncan/SNK) (default FALSE).
"rows" (metrics as rows, default) or "cols".
Decimal places for numeric output, default 4.
Decimal places for percentages, default 1.
Logical; in scope="cells", count only observed cells (drop NA). Default TRUE.