don't partialy match effect in model_parameters()

R/eta_squared-main.R

@@ -23,7 +23,7 @@
 #' @param verbose Toggle warnings and messages on or off.
 #' @inheritParams chisq_to_phi
 #' @param ... Arguments passed to or from other methods.
 #'   - Can be `include_intercept = TRUE` to include the effect size for the intercept (when it is included in the ANOVA table).
 #'   - For Bayesian models, arguments passed to `ss_function`.
 #'
 #' @return
@@ -248,7 +248,7 @@
                             ci = 0.95, alternative = "greater",
                             verbose = TRUE, ...) {
   alternative <- .match.alt(alternative, FALSE)
   out <- .anova_es(model, type = "epsilon", partial = partial, ci = ci, alternative = alternative, verbose = verbose, ...)
   class(out) <- unique(c("effectsize_anova", "effectsize_table", "see_effectsize_table", class(out)))
   if ("CI" %in% colnames(out)) attr(out, "ci_method") <- list(method = "ncp", distribution = "F")
   attr(out, "approximate") <- isTRUE(attr(out, "approximate", exact = TRUE))
@@ -294,7 +294,7 @@
 
   es_name <- get_effectsize_name(colnames(res))
   res[[es_name]] <- res[[es_name]] / (1 - res[[es_name]])
   if (grepl("_partial", es_name)) {
     colnames(res)[colnames(res) == es_name] <- "Cohens_f2_partial"
   } else {
     colnames(res)[colnames(res) == es_name] <- "Cohens_f2"
@@ -316,7 +316,7 @@
   if ("CI" %in% colnames(res)) attr(res, "ci_method") <- list(method = "ncp", distribution = "F")
   class(res) <- unique(c("effectsize_anova", "effectsize_table", "see_effectsize_table", class(res)))
   attr(res, "approximate") <- isTRUE(attr(res, "approximate", exact = TRUE))
   attr(res, "table_footer") <- if (method != "eta") sprintf("Based on %s squared.", paste0(toupper(substring(method, 1, 1)), substring(method, 2)))
   res
 }
 
@@ -430,7 +430,7 @@
 
 
   # Estimate effect size ---
   if (type == "eta") {
     if (isTRUE(generalized) || is.character(generalized)) {
       ## copied from afex
       obs <- logical(nrow(aov_table))
@@ -448,7 +448,7 @@
 
       aov_table$Eta2_generalized <- aov_table$Sum_Squares /
         (aov_table$Sum_Squares + values$Sum_Squares_residuals + obs_SSn1 - obs_SSn2)
     } else if (!isTRUE(partial)) {
       aov_table$Eta2 <- aov_table$Sum_Squares /
         values$Sum_Squares_total
     } else {
@@ -457,7 +457,7 @@
           (aov_table$Sum_Squares + values$Sum_Squares_residuals)
     }
   } else if (type == "omega") {
     if (!isTRUE(partial)) {
       aov_table$Omega2 <-
         (aov_table$Sum_Squares - aov_table$df * values$Mean_Square_residuals) /
           (values$Sum_Squares_total + values$Mean_Square_residuals)
@@ -469,7 +469,7 @@
       aov_table$Omega2_partial <- pmax(0, aov_table$Omega2_partial)
     }
   } else if (type == "epsilon") {
     if (!isTRUE(partial)) {
       aov_table$Epsilon2 <-
         (aov_table$Sum_Squares - aov_table$df * values$Mean_Square_residuals) /
           values$Sum_Squares_total
@@ -485,7 +485,7 @@
   out <- aov_table
 
   # Add CIs ---
   if (!is.null(ci)) {
     # based on MBESS::ci.R2
     ES <- pmax(0, out[[ncol(out)]])
     f <- (ES / out$df) / ((1 - ES) / df_error)
@@ -570,7 +570,7 @@
 
 
   # Estimate effect size ---
   if (type == "eta") {
     if (isTRUE(generalized) || is.character(generalized)) {
       ## copied from afex
       obs <- logical(nrow(aov_table))
@@ -833,7 +833,7 @@
       include_intercept = include_intercept
     )
 
-  attr(out, "anova_type") <- tryCatch(attr(parameters::model_parameters(model, verbose = FALSE, effects = "fixed"), "anova_type"),
+  attr(out, "anova_type") <- tryCatch(attr(parameters::model_parameters(model, verbose = FALSE, effects = "fixed", effectsize_type = NULL), "anova_type"),
     error = function(...) 1
   )
   attr(out, "approximate") <- TRUE
@@ -864,7 +864,7 @@
 
   # TODO this should be in .anova_es.anvoa
   # TODO the aoc method should convert to an anova table, then pass to anova
-  params <- parameters::model_parameters(model, verbose = verbose, effects = "fixed")
+  params <- parameters::model_parameters(model, verbose = verbose, effects = "fixed", effectsize_type = NULL)
   out <- .es_aov_simple(as.data.frame(params),
     type = type,
     partial = partial, generalized = generalized,
@@ -890,7 +890,7 @@
                               verbose = TRUE,
                               include_intercept = FALSE,
                               ...) {
-  params <- parameters::model_parameters(model, verbose = verbose, effects = "fixed")
+  params <- parameters::model_parameters(model, verbose = verbose, effects = "fixed", effectsize_type = NULL)
   anova_type <- attr(params, "anova_type")
   params <- as.data.frame(params)
 

R/eta_squared-methods.R

@@ -255,7 +255,7 @@
                            ci = 0.95, alternative = "greater",
                            verbose = TRUE,
                            ...) {
-  params <- parameters::model_parameters(model, verbose = verbose, effects = "fixed")
+  params <- parameters::model_parameters(model, verbose = verbose, effects = "fixed", effectsize_type = NULL)
   anova_type <- attr(params, "anova_type")
 
   params <- split(params, factor(params$Response, levels = unique(params$Response))) # make sure row order is not changed