Nested if else statements in R. Keep getting "Error: no function to return from, jumping to top level"

I know there are lots of questions like this around and tried the solutions proposed. But still I could not solve the following. My aim is to create a function in R which would correlate pairs of columns in data frame. Dependent on the number of pairwise complete observations it would use slightly different approaches. The problem here is no matter what I try, while declaring the function, I keep getting:

Error: no function to return from, jumping to top level

and

Error: unexpected '}' in "}"

Here is the function:

    corr.loop <- function(df, varsA, varsB, normal, nonnormal) {
    results <- matrix(ncol = 8)
    colnames(results) <- c("varA", "varB", "type", "complete.obs.n", "estimate", "p", "lower.CI", "upper.CI")
    for (i in 1:length(varsA)) {
    for (j in 1:length(varsB)) {

      if ( 
        pairwise.complete.obs.n(df[, varsA[i]], df[, varsB[j]]) < 3 
        ) {
        results <- rbind(results,
                         c(
                           varsA[i],
                           varsB[j],
                           NA,
                           pairwise.complete.obs.n(df[, varsA[i]], df[, varsB[j]]),
                           rep(NA, 4)
                         ))
      } else { 

        type <- ifelse( (varsA[i] %in% nonnormal | varsB[j] %in% nonnormal), "spearman", "pearson")

      cor.results <-  ifelse( 
          type == "pearson",
          cor.test(
            x = df[, varsA[i]],
            y = df[, varsB[j]],
            alternative = "two.sided",
            method = "pearson",
            exact = TRUE,
            conf.level = 0.95,
            continuity = TRUE
          ),
          cor.test(
            x = df[, varsA[i]],
            y = df[, varsB[j]],
            alternative = "two.sided",
            method = "spearman",
            exact = TRUE,
            conf.level = 0.95,
            continuity = TRUE
          )
        )

        if ( 
          pairwise.complete.obs.n(df[, varsA[i]], df[, varsB[j]]) = 3 
          ) {
          results <- rbind(
            results,
            c(
              varsA[i],
              varsB[j],
              type,
              pairwise.complete.obs.n(df[, varsA[i]], df[, varsB[j]]),
              cor.results$estimate,
              cor.results$p.value,
              NA,
              NA
            )
          )

        } else {
          results <- rbind(
            results,
            c(
              varsA[i],
              varsB[j],
              type,
              pairwise.complete.obs.n(df[, varsA[i]], df[, varsB[j]]),
              cor.results$estimate,
              cor.results$p.value,
              cor.results$conf.int[1],
              cor.results$conf.int[2]
            )
          )

        }
      }
    }
  }
    results <- as.data.frame(results[-1, ])
    results[, 1:ncol(results)] <- lapply(results[, 1:ncol(results)], as.character)
    results[, 4:ncol(results)] <- lapply(results[, 4:ncol(results)], as.numeric)
    return(results) 
    }

Is there something obvious I am missing? Seems I just need a fresh eye here. Thank you!