Fix find_formula.glmmPQL (#836)

* Fix find_formula.glmmPQL

* lintr

DESCRIPTION

@@ -1,7 +1,7 @@
 Type: Package
 Package: insight
 Title: Easy Access to Model Information for Various Model Objects
-Version: 0.19.7.1
+Version: 0.19.7.2
 Authors@R: 
     c(person(given = "Daniel",
              family = "Lüdecke",

NAMESPACE

@@ -121,6 +121,7 @@ S3method(find_formula,gee)
 S3method(find_formula,glht)
 S3method(find_formula,glimML)
 S3method(find_formula,glmm)
+S3method(find_formula,glmmPQL)
 S3method(find_formula,glmmTMB)
 S3method(find_formula,glmmadmb)
 S3method(find_formula,gls)

NEWS.md

@@ -5,6 +5,8 @@
 * Fixed issue in `get_loglikelihood()` for glm-models with binary outcome, where
   levels were defined in reversed order.
 
+* Fixed issue in `find_formula()` for models of class `glmmPQL` (package *MASS*).
+
 # insight 0.19.7
 
 ## General

R/find_formula.R

@@ -517,21 +517,21 @@ find_formula.afex_aov <- function(x, verbose = TRUE, ...) {
     dv <- attr(x, "dv")
     id <- attr(x, "id")
 
-    within <- names(attr(x, "within"))
-    within <- paste0(within, collapse = "*")
-    within <- paste0("(", within, ")")
-    e <- paste0("Error(", id, "/", within, ")")
+    within_variables <- names(attr(x, "within"))
+    within_variables <- paste0(within_variables, collapse = "*")
+    within_variables <- paste0("(", within_variables, ")")
+    e <- paste0("Error(", id, "/", within_variables, ")")
 
     between <- names(attr(x, "between"))
     if (length(between) > 0L) {
       tempf <- find_formula(x$lm)[[1]]
       between <- as.character(tempf)[3]
       between <- paste0("(", between, ")")
 
-      within <- paste0(c(within, between), collapse = "*")
+      within_variables <- paste0(c(within_variables, between), collapse = "*")
     }
 
-    out <- list(conditional = stats::formula(paste0(dv, "~", within, "+", e)))
+    out <- list(conditional = stats::formula(paste0(dv, "~", within_variables, "+", e)))
     class(out) <- c("insight_formula", "list")
     out
   }
@@ -600,12 +600,10 @@ find_formula.gls <- function(x, verbose = TRUE, ...) {
   }
 
   l <- tryCatch(
-    {
-      list(
-        conditional = stats::formula(x),
-        correlation = stats::as.formula(f_corr)
-      )
-    },
+    list(
+      conditional = stats::formula(x),
+      correlation = stats::as.formula(f_corr)
+    ),
     error = function(x) {
       NULL
     }
@@ -1267,6 +1265,16 @@ find_formula.sem <- function(x, verbose = TRUE, ...) {
 #' @export
 find_formula.lme <- function(x, verbose = TRUE, ...) {
   fm <- stats::formula(x$terms)
+  .find_formula_nlme(x, fm, verbose = verbose, ...)
+}
+
+#' @export
+find_formula.glmmPQL <- function(x, verbose = TRUE, ...) {
+  fm <- stats::formula(x)
+  .find_formula_nlme(x, fm, verbose = verbose, ...)
+}
+
+.find_formula_nlme <- function(x, fm, verbose = TRUE, ...) {
   fmr <- eval(x$call$random)
   if (!is.null(fmr) && safe_deparse(fmr)[1] == "~1") {
     check_if_installed("nlme")
@@ -1364,12 +1372,10 @@ find_formula.BBmm <- function(x, verbose = TRUE, ...) {
 #' @export
 find_formula.mmclogit <- function(x, verbose = TRUE, ...) {
   f <- tryCatch(
-    {
-      list(
-        conditional = stats::formula(x),
-        random = stats::as.formula(parse(text = safe_deparse(x$call))[[1]]$random)
-      )
-    },
+    list(
+      conditional = stats::formula(x),
+      random = stats::as.formula(parse(text = safe_deparse(x$call))[[1]]$random)
+    ),
     error = function(x) {
       NULL
     }
@@ -1418,12 +1424,10 @@ find_formula.stanreg <- function(x, verbose = TRUE, ...) {
     # special handling for stan_gamm4
     if (inherits(x, "gamm4")) {
       f.random <- tryCatch(
-        {
-          lapply(.findbars(stats::formula(x$glmod)), function(.x) {
-            f <- safe_deparse(.x)
-            stats::as.formula(paste0("~", f))
-          })
-        },
+        lapply(.findbars(stats::formula(x$glmod)), function(.x) {
+          f <- safe_deparse(.x)
+          stats::as.formula(paste0("~", f))
+        }),
         error = function(e) {
           NULL
         }
@@ -1484,8 +1488,8 @@ find_formula.MCMCglmm <- function(x, verbose = TRUE, ...) {
 find_formula.BFBayesFactor <- function(x, verbose = TRUE, ...) {
   if (.classify_BFBayesFactor(x) == "linear") {
     fcond <- utils::tail(x@numerator, 1)[[1]]@identifier$formula
-    dt <- utils::tail(x@numerator, 1)[[1]]@dataTypes
-    frand <- names(dt)[which(dt == "random")]
+    dat_types <- utils::tail(x@numerator, 1)[[1]]@dataTypes
+    frand <- names(dat_types)[which(dat_types == "random")]
 
     if (is_empty_object(frand)) {
       f.random <- NULL
@@ -1816,15 +1820,14 @@ find_formula.model_fit <- function(x, verbose = TRUE, ...) {
     fc <- try(.formula_clean(f[[1]]), silent = TRUE)
     if (inherits(fc, "try-error")) {
       format_error(attributes(fc)$condition$message)
-    } else {
-      if (verbose) {
-        format_warning(paste0(
-          "Using `$` in model formulas can produce unexpected results. Specify your model using the `data` argument instead.", # nolint
-          "\n  Try: ", fc$formula, ", data = ", fc$data
-        ))
-      }
-      return(FALSE)
     }
+    if (verbose) {
+      format_warning(paste0(
+        "Using `$` in model formulas can produce unexpected results. Specify your model using the `data` argument instead.", # nolint
+        "\n  Try: ", fc$formula, ", data = ", fc$data
+      ))
+    }
+    return(FALSE)
   }
   return(TRUE)
 }

tests/testthat/test-glmmPQL.R

@@ -0,0 +1,19 @@
+skip_if_not_installed("nlme")
+skip_if_not_installed("MASS")
+
+test_that("find_formula, get_data glmmPQL", {
+  example_dat <- data.frame(
+    prop = c(0.2, 0.2, 0.5, 0.7, 0.1, 1, 1, 1, 0.1),
+    size = c("small", "small", "small", "large", "large", "large", "large", "small", "small"),
+    x = c(0.1, 0.1, 0.8, 0.7, 0.6, 0.5, 0.5, 0.1, 0.1),
+    species = c("sp1", "sp1", "sp2", "sp2", "sp3", "sp3", "sp4", "sp4", "sp4"),
+    stringsAsFactors = FALSE
+  )
+
+  mn <- MASS::glmmPQL(prop ~ x + size,
+    random = ~ 1 | species,
+    family = "quasibinomial", data = example_dat
+  )
+  expect_identical(find_formula(mn)$conditional, as.formula("prop ~ x + size"))
+  expect_named(get_data(mn), c("prop", "x", "size", "species"))
+})