Draft FPC (#1193)

* Draft FPC

* fix

* error

* add FPC docs

* doc, add credits

* fix

* fix, add test

* fix

* news

* make it S3

* add more classes

* add default

* fixes

* document method

* news

* Use Matrix transpose, avoid as.matrix if possible

* cleanup

* docs

* fix

* fix tests

* alloe glmmTMB non mixed

* check no longer needed

* fix

* simplify script for test, add test for KR

Author: strengejacke

DESCRIPTION

@@ -1,7 +1,7 @@
 Type: Package
 Package: insight
 Title: Easy Access to Model Information for Various Model Objects
-Version: 1.5.0.9
+Version: 1.5.0.10
 Authors@R:
     c(person(given = "Daniel",
              family = "Lüdecke",

NAMESPACE

@@ -1889,6 +1889,11 @@ S3method(text_remove_backticks,matrix)
 S3method(trim_ws,data.frame)
 S3method(trim_ws,default)
 S3method(trim_ws,list)
+S3method(vcovFPC,default)
+S3method(vcovFPC,glm)
+S3method(vcovFPC,glmmTMB)
+S3method(vcovFPC,lm)
+S3method(vcovFPC,merMod)
 export(all_models_equal)
 export(all_models_same_class)
 export(broom_columns)
@@ -2015,3 +2020,4 @@ export(supported_models)
 export(text_remove_backticks)
 export(trim_ws)
 export(validate_argument)
+export(vcovFPC)

NEWS.md

@@ -18,6 +18,12 @@
 
 * `get_data()` now supports objects of class `mira` from package *mice*.
 
+* `get_varcov()` now supports the option `"fpc"` to apply finite population
+  correction (Lai et al. 2018).
+
+* Added a new function, `vcovFPC()`, to calculate finite-population-adjusted
+  variance-covariance matrices.
+
 ## Bug fixes
 
 * `has_intercept()` now correctly detects whether models from packages *fixest*

R/get_df.R

@@ -66,10 +66,10 @@
 #' and between-cluster effects. Note that this implementation does not return
 #' exactly the same results as shown in _Li and Redden 2015_, but similar.
 #'
-#' *Satterthwaite and Kenward-Rogers degrees of freedom*
+#' *Satterthwaite and Kenward-Roger degrees of freedom*
 #'
 #' Unlike simpler approximation heuristics like the "m-l-1" rule (`type = "ml1"`),
-#' the Satterthwaite or Kenward-Rogers approximation is also applicable in more
+#' the Satterthwaite or Kenward-Roger approximation is also applicable in more
 #' complex multilevel designs. However, the "m-l-1" or "between-within" heuristics
 #' also apply to generalized mixed models, while approaches like Kenward-Roger
 #' or Satterthwaite are limited to linear mixed models only.