⚡ Bolt: Replace sapply with vapply in llcont

.jules/bolt.md

@@ -15,3 +15,10 @@
 ## 2024-05-15 - [R Performance: ifelse Overhead]
 **Learning:** In R, ifelse evaluates both true and false branches entirely before subsetting, which is very inefficient for vector operations.
 **Action:** Optimize this by preallocating with res <- Y * 0 to preserve attributes and using vectorized subsetting like if any cond res subset <- ...
+## 2026-08-11 - [R Performance: ifelse vs Readability]
+**Learning:** In R, replacing `ifelse()` with vectorized subsetting (and its required `NA` handling and scalar recycling) can severely degrade code readability, turning a 1-liner into 7 lines.
+**Action:** Avoid this micro-optimization unless the specific `ifelse()` call is a proven, high-impact performance bottleneck.
+
+## 2026-08-11 - [R Performance: vapply over sapply]
+**Learning:** In R codebases, using `sapply` over a list involves significant overhead to deduce and simplify the return type.
+**Action:** When the return type and length are known, prefer `vapply(..., FUN.VALUE = type)` over `sapply(...)` for better performance and safety.

R/llcont.R

@@ -407,7 +407,7 @@ llcont.lavaan <- function(x, ...){
   if(tolower(lavInspect(x, "options")$missing) == "ml.x") stop("cannot handle lavaan models with missing='ml.x'. consider using missing='ml'.", call. = FALSE)
   mispatts <- lavInspect(x, "patterns")
   if(any(class(mispatts) == "list")){
-    npatts <- max(sapply(mispatts, nrow))
+    npatts <- max(vapply(mispatts, nrow, numeric(1)))
   } else {
     npatts <- nrow(mispatts)
   }