-#' Convenience functions for analyzing factorial experiments using ANOVA or mixed models. aov_ez(), aov_car(), and aov_4() allow specification of between, within (i.e., repeated-measures), or mixed between-within (i.e., split-plot) ANOVAs for data in long format (i.e., one observation per row), aggregating multiple observations per individual and cell of the design. mixed() fits mixed models using lme4::lmer() and computes p-values for all fixed effects using either Kenward-Roger or Satterthwaite approximation for degrees of freedom (LMM only), parametric bootstrap (LMMs and GLMMs), or likelihood ratio tests (LMMs and GLMMs). afex uses type 3 sums of squares as default (imitating commercial statistical software).
+#' Convenience functions for analyzing factorial experiments using ANOVA or mixed models.
+#' aov_ez(), aov_car(), and aov_4() allow specification of between, within (i.e.,
+#' repeated-measures), or mixed between-within (i.e., split-plot) ANOVAs for data in long format (i.e.,
+#' one observation per row), aggregating multiple observations per individual and cell of the
+#' design. mixed() fits mixed models using lme4::lmer() and computes p-values for all fixed
+#' effects using either Kenward-Roger or Satterthwaite approximation for degrees of freedom
+#' (LMM only), parametric bootstrap (LMMs and GLMMs), or likelihood ratio tests (LMMs and
+#' GLMMs). afex uses type 3 sums of squares as default (imitating commercial statistical software).
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