Merge pull request #153 from sfcheung/devel

0.1.14.16: Add pseudo_johnson_neyman()

DESCRIPTION

@@ -1,6 +1,6 @@
 Package: manymome
 Title: Mediation, Moderation and Moderated-Mediation After Model Fitting
-Version: 0.1.14.15
+Version: 0.1.14.16
 Authors@R:
     c(person(given = "Shu Fai",
            family = "Cheung",

NAMESPACE

@@ -32,6 +32,7 @@ S3method(print,indirect_list)
 S3method(print,indirect_proportion)
 S3method(print,lm_list)
 S3method(print,mc_out)
+S3method(print,pseudo_johnson_neyman)
 S3method(print,summary_lm_list)
 S3method(summary,lm_list)
 S3method(terms,lm_from_lavaan)
@@ -67,4 +68,5 @@ export(merge_mod_levels)
 export(mod_levels)
 export(mod_levels_list)
 export(plot_effect_vs_w)
+export(pseudo_johnson_neyman)
 export(total_indirect_effect)

NEWS.md

@@ -1,4 +1,4 @@
-# manymome 0.1.14.15
+# manymome 0.1.14.16
 
 ## New Features
 
@@ -62,6 +62,15 @@
   against a moderator, using the output
   of `cond_indirect_effects()`. (0.1.14.14 - 0.1.14.15)
 
+- Added `pseudo_johnson_neyman()`. It
+  used the pseudo Johnson-Neyman approach
+  (Hayes, 2022) to find the value of
+  a moderator at which the conditional
+  effect (direct or indirect) changes
+  from nonsignificant to significant
+  (or vice versa), based on the
+  confidence interval selected.
+   (0.1.14.16)
 
 ## Miscellaneous
 

R/cond_indirect.R

@@ -1338,7 +1338,7 @@ cond_indirect_effects <- function(wlevels,
         attr(out1, "est") <- est
         attr(out1, "implied_stats") <- implied_stats
         if (boot_ci) attr(out1, "boot_out") <- boot_out
-        if (mc_ci) attr(out1, "ci_out") <- ci_out
+        if (mc_ci) attr(out1, "mc_out") <- mc_out
         attr(out1, "prods") <- prods
         attr(out1, "x") <- x
         attr(out1, "y") <- y