diff --git a/R/collocationAnalysis.R b/R/collocationAnalysis.R
index 34dc550..c9b8695 100644
--- a/R/collocationAnalysis.R
+++ b/R/collocationAnalysis.R
@@ -1,6 +1,25 @@
 #' @include logging.R
 setGeneric("collocationAnalysis", function(kco, ...) standardGeneric("collocationAnalysis"))
 
+#' Keep only collocates that are attested often enough relative to expectation
+#'
+#' Rows without an expected frequency are kept, as are all rows if the ratio is
+#' 0 or `NULL`, which switches the filter off.
+#'
+#' @param result collocation analysis result
+#' @param minObservedExpectedRatio minimum ratio of observed to expected
+#'   co-occurrence frequency
+#' @return `result` without the rows that fall below the ratio
+#' @noRd
+filterByObservedExpectedRatio <- function(result, minObservedExpectedRatio) {
+  if (is.null(minObservedExpectedRatio) || is.na(minObservedExpectedRatio) ||
+    minObservedExpectedRatio <= 0 || nrow(result) == 0 ||
+    !all(c("O", "E") %in% names(result))) {
+    return(result)
+  }
+  result[is.na(result$E) | result$O >= minObservedExpectedRatio * result$E, , drop = FALSE]
+}
+
 #' Name of the attribute under which cache files record their analysis parameters
 #' @noRd
 collocationCacheAttribute <- "RKorAPClient.collocationAnalysis"
@@ -98,9 +117,19 @@
 #' @param threshold              minimum value of `thresholdScore` function call to apply collocation analysis recursively (only applied when \code{maxRecurse > 0}).
 #'   Note that the default score, `logDice`, expresses how salient a pair is
 #'   rather than how surprising, so that a frequent collocate can pass it while
-#'   co-occurring less often than expected. Adding `dplyr::filter(O > E)`, or a
-#'   minimum `pmi` or `ll`, removes those. See the "Salience versus surprise"
-#'   section of \code{\link{association-score-functions}}.
+#'   co-occurring less often than expected. `minObservedExpectedRatio` keeps
+#'   those out. See the "Salience versus surprise" section of
+#'   \code{\link{association-score-functions}}.
+#' @param minObservedExpectedRatio minimum ratio of observed to expected co-occurrence
+#'   frequency a collocate must reach. Defaults to 1, which keeps only collocates
+#'   that occur at least as often as expected by chance, corresponding to a
+#'   non-negative `pmi`. Without it, frequent words can end up among the top
+#'   collocates by `logDice` although the node does not attract them at all (see
+#'   the "Salience versus surprise" section of
+#'   \code{\link{association-score-functions}}). Raise it to demand a stronger
+#'   contrast, e.g. 2 for collocates occurring at least twice as often as
+#'   expected, or set it to 0 to switch the filter off and obtain the unfiltered
+#'   result of earlier versions, e.g. in order to study repulsion.
 #' @param localStopwords         vector of stopwords that will not be considered as collocates in the current function call, but that will not be passed to recursive calls
 #' @param collocateFilterRegex   allow only collocates matching the regular expression
 #' @param queryMissingScores     if TRUE, attempt to retrieve corpus-based association scores for vc/collocate combinations that would otherwise be imputed, by re-querying the KorAP backend without applying the collocate frequency threshold
@@ -224,6 +253,7 @@
            threshold = 2.0,
            localStopwords = c(),
            collocateFilterRegex = "^[:alnum:]+-?[:alnum:]*$",
+           minObservedExpectedRatio = 1,
            queryMissingScores = FALSE,
            missingScoreQuantile = 0.05,
            vcLabel = NA_character_,
@@ -308,6 +338,7 @@
           node = node,
           vc = vc,
           minOccur = minOccur,
+          minObservedExpectedRatio = minObservedExpectedRatio,
           leftContextSize = leftContextSize,
           rightContextSize = rightContextSize,
           topCollocatesLimit = topCollocatesLimit,
@@ -402,6 +433,7 @@
           ...
         ) |>
           filter(O >= minOccur) |>
+          filterByObservedExpectedRatio(minObservedExpectedRatio) |>
           dplyr::arrange(dplyr::desc(logDice))
       } else {
         tibble()
@@ -433,6 +465,7 @@
           rightContextSize = rightContextSize,
           withinSpan = withinSpan,
           maxRecurse = maxRecurse - 1,
+          minObservedExpectedRatio = minObservedExpectedRatio,
           stopwords = stopwords,
           localStopwords = recurseWith$collocate,
           exactFrequencies = exactFrequencies,
@@ -456,6 +489,7 @@
 
         result <- result |>
           filter(O >= minOccur) |>
+          filterByObservedExpectedRatio(minObservedExpectedRatio) |>
           dplyr::arrange(dplyr::desc(logDice))
       }
     }