version 0.2.10

cran · Feb 23, 2024 · e9b58eb · e9b58eb
1 parent e3b7572
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diff --git a/DESCRIPTION b/DESCRIPTION
@@ -1,6 +1,6 @@
 Package: stdmod
 Title: Standardized Moderation Effect and Its Confidence Interval
-Version: 0.2.9
+Version: 0.2.10
 Authors@R: 
     c(person(given = "Shu Fai",
            family = "Cheung",
@@ -22,15 +22,15 @@ BugReports: https://github.com/sfcheung/stdmod/issues
 License: GPL-3
 Encoding: UTF-8
 LazyData: true
-RoxygenNote: 7.2.3
+RoxygenNote: 7.3.1
 Suggests: testthat, knitr, rmarkdown, visreg, lm.beta
 Depends: R (>= 4.0.0)
 Imports: boot, ggplot2, stats, utils, lavaan, manymome, rlang
 VignetteBuilder: knitr
 NeedsCompilation: no
-Packaged: 2023-09-11 11:30:09 UTC; sfcheung
+Packaged: 2024-02-22 13:26:37 UTC; sfcheung
 Author: Shu Fai Cheung [aut, cre] (<https://orcid.org/0000-0002-9871-9448>),
   David Weng Ngai Vong [ctb]
 Maintainer: Shu Fai Cheung <shufai.cheung@gmail.com>
 Repository: CRAN
-Date/Publication: 2023-09-11 14:10:02 UTC
+Date/Publication: 2024-02-22 14:10:02 UTC
diff --git a/MD5 b/MD5
@@ -1,10 +1,10 @@
-8e3ed4e5c3120c92172361986ac46cf4 *DESCRIPTION
-84d58b755ec05446d92870081518805d *NAMESPACE
-6e4c9cad544cfb77e693e8e73494e08a *NEWS.md
+6d88250e3ec6833a1536bacfa81ef358 *DESCRIPTION
+f5612283ed58f6203f842393def5c22a *NAMESPACE
+df72c8e0a592b04036fa40898b3f9882 *NEWS.md
 c91012ec543a1d47a5f0676fc59c49e4 *R/add1_stdmod.R
 dabd63219c02abc577b7ccc3b63330ea *R/coef_condeff.R
 d813390126f8534f38f7c9497d717f95 *R/coef_stdmod_lavaan.R
-39e569056326a758809369c18cd47857 *R/condeff.R
+b8d030ec435c9b60cf77128c25a51513 *R/condeff.R
 d6938324e28a6c3aeaba524d45a32b97 *R/condeff_boot.R
 ce833597ea9cab7a7f571788b1f2b69b *R/confint_condeff.R
 c7906d55a49c4dd79c452bc63fd1af94 *R/confint_stdmod.R
@@ -14,26 +14,26 @@ bcb17baebae7df70b1db3fef7fb27f33 *R/data_2.R
 b819d8629b065aab2f664e5f47a023ce *R/data_3.R
 49b5410e95b7747809ed3ad1911ab86c *R/data_4.R
 687854d151b006cdd910d6f6bdfee6ec *R/helpers.R
-9dae6709bd8d4e73d8727b89c4071d42 *R/plotmod.R
+d2dba9a32d4c52825e51d89da6b7b40b *R/plotmod.R
 436a80d659ba0c1cc1d04f24f4eb91f0 *R/plotmod_helpers.R
 f94d22597a6b0de284fa6a96871d3299 *R/plotmod_helpers_2.R
 dbbfb6f352b94f6eff13decaea3bf62c *R/print_cond_eff.R
 6d1e26948567c8d37108b1bb8d6adc8a *R/print_stdmod.R
 40bacea7c71b852f53d6de215d4ef709 *R/print_stdmod_lavaan.R
-fa608b4a8a98987c842f2d97315a2524 *R/print_summary_stdmod.R
+c1df4287a32b0169979be556e8ee0a03 *R/print_summary_stdmod.R
 8dc85d9a885415575f66ea5f330f5353 *R/std_selected.R
 a5de0499adb12177a8875e7f6d032451 *R/std_selected_boot.R
 1cb169eb2acf4fac9bbee453abe220de *R/stdmod-package.R
 582687ed0f63ef323470db4643ea7d66 *R/stdmod.R
 f94c6ce9a91686b315a67d30fc57622d *R/stdmod_bootci.R
 f3c64e8811a9daa4e3252b02a212e5e4 *R/stdmod_lavaan.R
-1eb65f93ba1ea4383f02beed9b277acb *R/summary_stdmod.R
+71533d9957cb2ccecb2a1fd94b011de0 *R/summary_stdmod.R
 fbdb46b8f7b74a8f9cf683552fc62c12 *R/sweep2.R
-828d5dc9e324c120eb600c0d6aaef4f2 *R/update_stdmod.R
+a72daa571e2b0c95c6c7513f551865fa *R/update_stdmod.R
 22421b57671dae1837ae82e6e9bfd4a5 *R/vcov_stdmod.R
-ba75730b942c26b7a21dc29ae3885138 *README.md
-2836b2c5db38c9819380bd093383d89d *build/partial.rdb
-73747744a9763e54ea1ff25191855195 *build/vignette.rds
+fcb19f43597a5c4952eb3dd44e498d5c *README.md
+b943a1546a1e17be4eea235ec7b4616b *build/partial.rdb
+f134b5fbe12ed83b63d3a665c54d6367 *build/vignette.rds
 cfac528a204b0a0ae0235a1f99bafb6a *data/sleep_emo_con.rda
 f1f88af1d468fc13dca3e58e09e7c83a *data/test_mod1.rda
 7b8802b1880748751497209ff8ca2362 *data/test_mod2.rda
@@ -45,37 +45,37 @@ d8e41d1a7cc5addf942e6b195e7c1234 *data/test_x_1_w_1_v_1_cat1_n_500.rda
 3faf7434efb51873a4810b1dcc0f0e06 *inst/CITATION
 73a9eceb039d8ed57db5d33ccfe5ad48 *inst/doc/cond_effect.Rmd
 8e599016d126cb89d12e06c007240554 *inst/doc/cond_effect.html
-e73069c427d036a04fd3aecfef7f8f3d *inst/doc/moderation.R
+43250abdb6be9c06801b9e3c2dcf9167 *inst/doc/moderation.R
 4c927d744634fe6f5fcb9caae23e138c *inst/doc/moderation.Rmd
-2d5c44f03c1ead62689a2cb4aac4f5dd *inst/doc/moderation.html
-0e21aa9bed1d163a7dbb95b1a5c8d5fe *inst/doc/plotmod.R
+846b9ea6d1447ad8168f3bd90b2cb814 *inst/doc/moderation.html
+de62b6958b6ebc23a2d1c81c421a6f0a *inst/doc/plotmod.R
 e9168b3410d5be28dd5138111908ae1b *inst/doc/plotmod.Rmd
-217796e00d43f1a117da02412a100c8a *inst/doc/plotmod.html
-57d8f7d5d6426fb662e7fcd4531fd50f *inst/doc/std_selected.R
+41101be85275e3316376f84d25c34fb0 *inst/doc/plotmod.html
+440596292906dfb9234f99db0078ff5f *inst/doc/std_selected.R
 fb0927ee277d4f7981bc473829c4341c *inst/doc/std_selected.Rmd
-4ba60e95666279890ad83cfc252ddaba *inst/doc/std_selected.html
-1099cc957a4a6c6ac75f81ce4a0280f8 *inst/doc/stdmod.R
+43981e888dea6a3e7f4a2e42f5ccc8e3 *inst/doc/std_selected.html
+ea304269c32b44bf366d63813e77203a *inst/doc/stdmod.R
 6541b8b78f7b5c95c5151a81eb838fb1 *inst/doc/stdmod.Rmd
-726a2a1f6565c9b6d2364e7cf5e59646 *inst/doc/stdmod.html
-0360b8dce832ccc14f306b938b303f1b *inst/doc/stdmod_lavaan.R
+7af8a163e4d8b2bb24846d1916016f02 *inst/doc/stdmod.html
+f63dbce088afcffe244ad962eff5db1c *inst/doc/stdmod_lavaan.R
 c791bdd1939f6b284c31c817af259ebb *inst/doc/stdmod_lavaan.Rmd
-8caa0ee07dd3776540a6602f1d2898f7 *inst/doc/stdmod_lavaan.html
+1c0a02fa9308d0f17d3dfdfcb5a01488 *inst/doc/stdmod_lavaan.html
 e4cc05d13f860685b23f976542a241ba *man/add1.std_selected.Rd
 0f406a5327f9e87c2677e1427acea0f6 *man/coef.cond_effect.Rd
 c108330ccd79cd6f63d864a462aea078 *man/coef.stdmod_lavaan.Rd
-e659c642f668da1b5e3a9fff360c186c *man/cond_effect.Rd
+35975cb64dccb1e99eb685236695d63a *man/cond_effect.Rd
 795d16c4d387ce0cd29a7a0e64248307 *man/confint.cond_effect.Rd
 c3654c6f0355f5a4cd9f15b1bb99ae4e *man/confint.std_selected.Rd
 f2743f33206293bf12eb7cb969b53be4 *man/confint.stdmod_lavaan.Rd
 bb82e296e58d2ea526ae3f656c9ad2c0 *man/figures/logo.png
-bfe49e3c62ff4f7bbd5b335759c1206e *man/plotmod.Rd
+a963076cd91ef3abfb5230514249e89b *man/plotmod.Rd
 1b169ca01ea84708be6288efe9a4e674 *man/print.cond_effect.Rd
 7a5ea08bac5422af15d6116f3889c2b7 *man/print.std_selected.Rd
 8fb33c898d6066932fc76b3c13708c13 *man/print.stdmod_lavaan.Rd
 f5e487b4cd46a3c8b0d32434c6cbcd23 *man/print.summary.std_selected.Rd
 3f5183cfef6a509a391c972386ddec31 *man/sleep_emo_con.Rd
 ab61678dcb1af28f24c860b913ef3c28 *man/std_selected.Rd
-27a58940e43ae87a56bbf68fbe4a8fc1 *man/stdmod-package.Rd
+911859903b700a24577587a2a9af2007 *man/stdmod-package.Rd
 6bac7bd9b0026fc8f4a6512d26d06097 *man/stdmod.Rd
 6837efd969c2734c39fad15ce7e84b04 *man/stdmod_lavaan.Rd
 34638a9746f61ae47249437d53c03ca8 *man/summary.std_selected.Rd
@@ -93,10 +93,12 @@ ef5a016dfb84e5a0b807214950e8cc12 *man/test_x_1_w_1_v_2_n_500.Rd
 6e847adbb57cfae6c8db5405034735bd *tests/testthat/test_condeff_boot.R
 53e541030c06662d65209e6f11b3eaf9 *tests/testthat/test_condeff_boot_methods.R
 8fbc0aff90b2f4d0f14b1982a9a2ae4a *tests/testthat/test_condeff_methods.R
+0ab8ae971f58a373f05f872f32651579 *tests/testthat/test_condeff_user_value.R
 d8833fdc2c45cd8d204b8fc3d7214fc8 *tests/testthat/test_methods_stdmod_lavaan.R
 2da4234c4ecda23ee99caf953a99a5ae *tests/testthat/test_plotmod.R
 1a5c74f3f30a1e5452c0f4f00d86bae1 *tests/testthat/test_plotmod_percentile_more_levels.R
 a6915c8ac83a614ca673467b0aa4e7ea *tests/testthat/test_plotmod_tumble.R
+aeb58ab43abb69c3744fe23f54237782 *tests/testthat/test_plotmod_user_value.R
 66a05a4f86230a6dad0e33fc1999a7b0 *tests/testthat/test_stdmod.R
 ae024e39fa03a714e4095a36f5e6d36e *tests/testthat/test_stdmod_cat.R
 cf2313e1050b1e0bbe62a3c98b3d9aae *tests/testthat/test_stdmod_lavaan.R
@@ -109,6 +111,7 @@ ce14ffeb97dd862eeb2a52b4bec8a549 *tests/testthat/test_stdmod_lavaan_2.R
 a20f09dcf7ba6ab243e2c70b2429e4e4 *tests/testthat/test_stdmod_selected_confint.R
 a48b3233ecd66001c173f098364ce25b *tests/testthat/test_stdmod_selected_fac.R
 3fbce7cd8dfe2a25d9fd701602acb80a *tests/testthat/test_stdmod_selected_print_summary.R
+3b6de8af9aac71691c0c23f1dc941350 *tests/testthat/test_stdmod_selected_print_summary_rsq.R
 306aa52355cc517ca587f6352dbf476f *tests/testthat/test_stdmod_selected_update.R
 436288a2f8303dc81863cb2cb765e0b7 *tests/testthat/test_stdmod_selected_vcov.R
 26295d6ce031783107376927e1088383 *tests/testthat/test_stdmod_selectedj_to_std.R

diff --git a/NAMESPACE b/NAMESPACE
@@ -22,3 +22,4 @@ export(stdmod)
 export(stdmod_boot)
 export(stdmod_lavaan)
 importFrom(rlang,.data)
+importFrom(stats,anova)
diff --git a/NEWS.md b/NEWS.md
@@ -1,3 +1,31 @@
+# stdmod 0.2.10
+
+## New Features
+
+- Improved the printout of the `summary()`
+  of `std_selected()`
+  and `std_selected_boot()` outputs.
+  It now prints the R-squared increase
+  of the highest order term, as well as
+  the *F* test for the increase, if the
+  model has one and only one highest
+  order term (e.g., an interaction
+  term). (0.2.9.1)
+
+- Added the argument `w_values` to
+  `cond_effect()` and `plolmod()`.
+  Users can specify the
+  values of the moderator (`w`)
+  to be used to compute the conditional
+  effects. (0.2.9.2)
+
+## Miscellaneous
+
+- Revised `update.std_selected()`. Though
+  still not recommended, it should now
+  work more reliably if it needs to be
+  called. (0.2.9.1)
+
 # stdmod 0.2.9
 
 - Fixed the issue with `stdmod-package`. (0.2.8.9001)

diff --git a/R/condeff.R b/R/condeff.R
@@ -102,6 +102,19 @@
 #'                          "high" for the moderator. Default is 1.
 #'                          Ignored if `w` is categorical.
 #'
+#' @param w_values The values of `w` to
+#' be used. Default is `NULL`. If a
+#' numeric vector is supplied, these
+#' values will be used to compute the
+#' conditional effects. Other arguments
+#' on generating levels are ignored.
+#' Note that, if `w` has been standardized
+#' or centered, these values are for
+#' the standardized or centered `w`.
+#' The values will always be sorted.
+#' This argument is ignored if `w` is
+#' categorical.
+#'
 #' @author Shu Fai Cheung <https://orcid.org/0000-0002-9871-9448>
 #'
 #'
@@ -133,7 +146,8 @@ cond_effect <- function(output,
                       w_method = c("sd", "percentile"),
                       w_percentiles = c(.16, .50, .84),
                       w_sd_to_percentiles = NA,
-                      w_from_mean_in_sd = 1
+                      w_from_mean_in_sd = 1,
+                      w_values = NULL
                       ) {
     mf0 <- stats::model.frame(output)
     w_method <- match.arg(w_method)
@@ -165,15 +179,20 @@ cond_effect <- function(output,
         class(output0) <- tmp[!(tmp %in% "std_selected")]
       }
     if (w_numeric) {
-        w_levels <- gen_levels(mf0[, w],
-                              method = w_method,
-                              from_mean_in_sd = w_from_mean_in_sd,
-                              levels = c(-1, 0, 1),
-                              sd_levels = c(-1, 0, 1),
-                              sd_to_percentiles = w_sd_to_percentiles,
-                              percentiles = w_percentiles)
-        w_levels <- sort(w_levels, decreasing = TRUE)
-        w_levels_labels <- c("High", "Medium", "Low")
+        if (is.numeric(w_values)) {
+            w_levels <- sort(w_values, decreasing = TRUE)
+            w_levels_labels <- as.character(w_levels)
+          } else {
+            w_levels <- gen_levels(mf0[, w],
+                                  method = w_method,
+                                  from_mean_in_sd = w_from_mean_in_sd,
+                                  levels = c(-1, 0, 1),
+                                  sd_levels = c(-1, 0, 1),
+                                  sd_to_percentiles = w_sd_to_percentiles,
+                                  percentiles = w_percentiles)
+            w_levels <- sort(w_levels, decreasing = TRUE)
+            w_levels_labels <- c("High", "Medium", "Low")
+          }
       } else {
         w_levels <- levels(as.factor(mf0[, w]))
         w_levels_labels <- w_levels

diff --git a/R/plotmod.R b/R/plotmod.R
@@ -117,6 +117,20 @@
 #'                            `x_sd_to_percentiles` is set to 1, then the lower
 #'                            and upper percentiles are 16th and 84th,
 #'                            respectively. Default is `NA`.
+#'
+#' @param w_values The values of `w` to
+#' be used. Default is `NULL`. If a
+#' numeric vector is supplied, these
+#' values will be used to compute the
+#' conditional effects. Other arguments
+#' on generating levels are ignored.
+#' Note that, if `w` has been standardized
+#' or centered, these values are for
+#' the standardized or centered `w`.
+#' The values will always be sorted.
+#' This argument is ignored if `w` is
+#' categorical.
+#'
 #' @param note_standardized If `TRUE`, will check whether a variable has SD
 #'                          nearly equal to one. If yes, will report this in the
 #'                          plot.
@@ -192,6 +206,7 @@ plotmod <- function(output, x, w,
                             x_percentiles = c(.16, .84),
                             w_sd_to_percentiles = NA,
                             x_sd_to_percentiles= NA,
+                            w_values = NULL,
                             note_standardized = TRUE,
                             no_title = FALSE,
                             line_width = 1,
@@ -225,32 +240,37 @@ plotmod <- function(output, x, w,
         stop("x variable must be a numeric variable.")
       }
     if (w_numeric) {
-        w_levels <- gen_levels(mf0[, w],
-                              method = w_method,
-                              from_mean_in_sd = w_from_mean_in_sd,
-                              levels = c(-1, 1),
-                              sd_levels = c(-1, 1),
-                              sd_to_percentiles = w_sd_to_percentiles,
-                              percentiles = w_percentiles)
-        tmp <- length(w_levels)
-        if (tmp == 2) {
-          w_levels_labels <- c("Low", "High")
-        }
-        if (tmp == 3) {
-          w_levels_labels <- c("Low", "Medium", "High")
-        }
-        if (tmp > 3) {
-          if (w_method == "percentile") {
-              w_levels_labels <- paste0(formatC(w_percentiles * 100,
-                                                digits = 0,
-                                                format = "f"),
-                                        "%")
-            } else {
-              w_levels_labels <- formatC(w_levels,
-                                         digits = 2,
-                                         format = "f")
+        if (is.numeric(w_values)) {
+            w_levels <- sort(w_values, decreasing = TRUE)
+            w_levels_labels <- as.character(w_levels)
+          } else {
+            w_levels <- gen_levels(mf0[, w],
+                                  method = w_method,
+                                  from_mean_in_sd = w_from_mean_in_sd,
+                                  levels = c(-1, 1),
+                                  sd_levels = c(-1, 1),
+                                  sd_to_percentiles = w_sd_to_percentiles,
+                                  percentiles = w_percentiles)
+            tmp <- length(w_levels)
+            if (tmp == 2) {
+              w_levels_labels <- c("Low", "High")
+            }
+            if (tmp == 3) {
+              w_levels_labels <- c("Low", "Medium", "High")
             }
-        }
+            if (tmp > 3) {
+              if (w_method == "percentile") {
+                  w_levels_labels <- paste0(formatC(w_percentiles * 100,
+                                                    digits = 0,
+                                                    format = "f"),
+                                            "%")
+                } else {
+                  w_levels_labels <- formatC(w_levels,
+                                            digits = 2,
+                                            format = "f")
+                }
+            }
+          }
       } else {
         w_lo <- NA
         w_hi <- NA

diff --git a/R/print_summary_stdmod.R b/R/print_summary_stdmod.R
@@ -171,6 +171,19 @@ print.summary.std_selected <- function(x, ...,
                        p_digits = ceiling(-log10(pvalue_less_than)))
       cat("\n")
     }
+  if (!is.na(x$highest_order) && !identical(x$f_highest, NA)) {
+      rsq_highest <- formatC(x$f_highest[2, "R.sq.change"],
+                             digits = est_digits,
+                             format = "f")
+      cat("= Test the highest order term =",
+          paste0("The highest order term             : ", x$highest_order),
+          paste0("R-squared increase adding this term: ", rsq_highest),
+          sep = "\n")
+      print_fstatistic_change(x$f_highest,
+                              f_digits = t_digits,
+                              p_digits = ceiling(-log10(pvalue_less_than)))
+      cat("\n")
+    }
   tmp <- character(0)
   if (scaled_or_centered) {
       tmp1 <- paste("- Estimates and their statistics are based on the data after",
@@ -241,12 +254,36 @@ print_fstatistic <- function(fstatistic,
      p <- stats::pf(f, df1, df2, lower.tail = FALSE)
      p_txt <- format_pvalue(p,
                             eps = 10^(-p_digits))
+     if (!grepl("^<", p_txt)) {
+        p_txt <- paste0("= ", p_txt)
+       }
      cat("ANOVA test of R-squared  : ",
          f_txt, ", p ", p_txt, "\n", sep = "")
   }
 
 #' @noRd
 
+print_fstatistic_change <- function(fstatistic,
+                                    f_digits = 4,
+                                    p_digits = 3) {
+     f <- fstatistic[2, "F"]
+     df1 <- fstatistic[2, "Df"]
+     df2 <- fstatistic[2, "Res.Df"]
+     f_txt <- paste0("F(",
+                     df1, ", ", df2, ") = ",
+                     round(f, f_digits))
+     p <- fstatistic[2, "Pr(>F)"]
+     p_txt <- format_pvalue(p,
+                            eps = 10^(-p_digits))
+     if (!grepl("^<", p_txt)) {
+        p_txt <- paste0("= ", p_txt)
+       }
+     cat("F test of R-squared increase       : ",
+         f_txt, ", p ", p_txt, "\n", sep = "")
+  }
+
+#' @noRd
+
 format_pvalue <- function(p,
                           eps = 1e-3) {
     p_digits <- ceiling(-log10(eps))