lintr

R/compute_variances.R

@@ -140,15 +140,15 @@
 
 
   compact_list(list(
-    "var.fixed" = var.fixed,
-    "var.random" = var.random,
-    "var.residual" = var.residual,
-    "var.distribution" = var.distribution,
-    "var.dispersion" = var.dispersion,
-    "var.intercept" = var.intercept,
-    "var.slope" = var.slope,
-    "cor.slope_intercept" = cor.slope_intercept,
-    "cor.slopes" = cor.slopes
+    var.fixed = var.fixed,
+    var.random = var.random,
+    var.residual = var.residual,
+    var.distribution = var.distribution,
+    var.dispersion = var.dispersion,
+    var.intercept = var.intercept,
+    var.slope = var.slope,
+    cor.slope_intercept = cor.slope_intercept,
+    cor.slopes = cor.slopes
   ))
 }
 
@@ -308,12 +308,12 @@
     vc <- lapply(names(lme4::VarCorr(x)), function(i) {
       element <- lme4::VarCorr(x)[[i]]
       if (i != "residual__") {
-        if (!is.null(element$cov)) {
-          out <- as.matrix(drop(element$cov[, 1, ]))
-          colnames(out) <- rownames(out) <- gsub("Intercept", "(Intercept)", rownames(element$cov), fixed = TRUE)
-        } else {
+        if (is.null(element$cov)) {
           out <- as.matrix(drop(element$sd[, 1])^2)
           colnames(out) <- rownames(out) <- gsub("Intercept", "(Intercept)", rownames(element$sd), fixed = TRUE)
+        } else {
+          out <- as.matrix(drop(element$cov[, 1, ]))
+          colnames(out) <- rownames(out) <- gsub("Intercept", "(Intercept)", rownames(element$cov), fixed = TRUE)
         }
         attr(out, "sttdev") <- element$sd[, 1]
       } else {
@@ -600,7 +600,9 @@
   .null_model <- null_model(x, verbose = verbose)
 
   # check if null-model could be computed
-  if (!is.null(.null_model)) {
+  if (is.null(.null_model)) {
+    mu <- NA
+  } else {
     if (inherits(.null_model, "cpglmm")) {
       # installed?
       check_if_installed("cplm")
@@ -609,8 +611,6 @@
       null_fixef <- unname(.collapse_cond(lme4::fixef(.null_model)))
     }
     mu <- exp(null_fixef)
-  } else {
-    mu <- NA
   }
 
   if (is.na(mu)) {

R/find_formula.R

@@ -564,14 +564,14 @@ find_formula.RM <- find_formula.MANOVA
 find_formula.gls <- function(x, verbose = TRUE, ...) {
   ## TODO this is an intermediate fix to return the correlation variables from gls-objects
   fcorr <- x$call$correlation
-  if (!is.null(fcorr)) {
+  if (is.null(fcorr)) {
+    f_corr <- NULL
+  } else {
     if (inherits(fcorr, "name")) {
       f_corr <- attributes(eval(fcorr))$formula
     } else {
       f_corr <- parse(text = safe_deparse(fcorr))[[1]]
     }
-  } else {
-    f_corr <- NULL
   }
   if (is.symbol(f_corr)) {
     f_corr <- paste("~", safe_deparse(f_corr))
@@ -1272,14 +1272,14 @@ find_formula.lme <- function(x, verbose = TRUE, ...) {
   }
   ## TODO this is an intermediate fix to return the correlation variables from lme-objects
   fcorr <- x$call$correlation
-  if (!is.null(fcorr)) {
+  if (is.null(fcorr)) {
+    fc <- NULL
+  } else {
     if (inherits(fcorr, "name")) {
       fc <- attributes(eval(fcorr))$formula
     } else {
       fc <- parse(text = safe_deparse(fcorr))[[1]]$form
     }
-  } else {
-    fc <- NULL
   }
 
   f <- compact_list(list(
@@ -1313,11 +1313,11 @@ find_formula.mixor <- function(x, verbose = TRUE, ...) {
   f_id <- deparse(x$call$id)
   f_rs <- x$call$which.random.slope
 
-  if (!is.null(f_rs)) {
+  if (is.null(f_rs)) {
+    fmr <- f_id
+  } else {
     f_rs <- trim_ws(unlist(strsplit(safe_deparse(x$call$formula[[3]]), "+", fixed = TRUE), use.names = FALSE))[f_rs]
     fmr <- paste(f_rs, "|", f_id)
-  } else {
-    fmr <- f_id
   }
 
   fmr <- stats::as.formula(paste("~", fmr))
@@ -1489,7 +1489,10 @@ find_formula.BFBayesFactor <- function(x, verbose = TRUE, ...) {
     dt <- utils::tail(x@numerator, 1)[[1]]@dataTypes
     frand <- names(dt)[which(dt == "random")]
 
-    if (!is_empty_object(frand)) {
+    if (is_empty_object(frand)) {
+      f.random <- NULL
+      f.cond <- stats::as.formula(fcond)
+    } else {
       f.random <- stats::as.formula(paste0("~", paste(frand, collapse = " + ")))
       for (i in frand) {
         fcond <- sub(i, "", fcond, fixed = TRUE)
@@ -1505,9 +1508,6 @@ find_formula.BFBayesFactor <- function(x, verbose = TRUE, ...) {
         fcond <- paste(fcond, "1")
       }
       f.cond <- stats::as.formula(trim_ws(fcond))
-    } else {
-      f.random <- NULL
-      f.cond <- stats::as.formula(fcond)
     }
   } else if (.classify_BFBayesFactor(x) %in% c("ttest1", "ttest2")) {
     f.cond <- .safe(stats::as.formula(x@numerator[[1]]@identifier$formula))

R/find_parameters_bayesian.R

@@ -48,10 +48,10 @@ find_parameters.BGGM <- function(x,
                                  ...) {
   component <- match.arg(component)
   l <- switch(component,
-    "correlation" = list(correlation = colnames(get_parameters(x, component = "correlation"))),
-    "conditional" = list(conditional = colnames(get_parameters(x, component = "conditional"))),
-    "intercept" = list(intercept = colnames(x$Y)),
-    "all" = list(
+    correlation = list(correlation = colnames(get_parameters(x, component = "correlation"))),
+    conditional = list(conditional = colnames(get_parameters(x, component = "conditional"))),
+    intercept = list(intercept = colnames(x$Y)),
+    all = list(
       intercept = colnames(x$Y),
       correlation = colnames(get_parameters(x, component = "correlation")),
       conditional = colnames(get_parameters(x, component = "conditional"))
@@ -549,7 +549,7 @@ find_parameters.stanmvreg <- function(x,
   }
 
 
-  l <- mapply(c, l.cond, l.random, l.sigma, SIMPLIFY = FALSE)
+  l <- Map(c, l.cond, l.random, l.sigma)
   l <- .filter_pars(l, parameters, is_mv = TRUE)
 
   effects <- match.arg(effects)

R/format_table.R

@@ -516,7 +516,7 @@ format_table <- function(x,
       other_ci_colname <- sprintf("%s %g%% CI", other, unique(stats::na.omit(att[[paste0("ci_", other)]])) * 100)
     } else if (!is.null(att[["ci"]])) {
       other_ci_colname <- sprintf("%s %g%% CI", other, unique(stats::na.omit(att[["ci"]])) * 100)
-    } else if (length(other == 1) && paste0(other, "_CI") %in% colnames(x)) {
+    } else if (length(other) == 1 && paste0(other, "_CI") %in% colnames(x)) {
       other_ci_colname <- sprintf("%s %g%% CI", other, unique(stats::na.omit(x[[paste0(other, "_CI")]])) * 100)
     } else {
       other_ci_colname <- paste(other, " CI")