diff --git a/DESCRIPTION b/DESCRIPTION
index a0ba94450..034cd4fe0 100644
--- a/DESCRIPTION
+++ b/DESCRIPTION
@@ -43,7 +43,6 @@ Imports:
     rlang,
     SqlRender (>= 1.1.3),
     survival,
-    tibble,
     tidyr,
     utils
 Suggests:
@@ -77,6 +76,6 @@ Remotes:
     ohdsi/IterativeHardThresholding,
     ohdsi/ParallelLogger,
     ohdsi/ShinyAppBuilder,
-    ohdsi/ResultModelManager
+    ohdsi/ResultModelManager,
 RoxygenNote: 7.2.3
 Encoding: UTF-8
diff --git a/R/AndromedaHelperFunctions.R b/R/AndromedaHelperFunctions.R
index bf70bdb06..b6182610c 100644
--- a/R/AndromedaHelperFunctions.R
+++ b/R/AndromedaHelperFunctions.R
@@ -97,7 +97,7 @@ calculatePrevs <- function(plpData, population){
   #===========================
   
   # add population to sqllite
-  population <- tibble::as_tibble(population)
+  population <- dplyr::as_tibble(population)
   plpData$covariateData$population <- population %>% 
     dplyr::select("rowId", "outcomeCount")
   
diff --git a/R/FeatureImportance.R b/R/FeatureImportance.R
index f47f4de25..b5a469bc2 100644
--- a/R/FeatureImportance.R
+++ b/R/FeatureImportance.R
@@ -200,7 +200,7 @@ permute <- function(plpDataLocation,cId,population){
   
     # find a new random selection of people and give them the covariate and value
     newPlp <- sample(population$rowId,nSamp)
-    newData <- tibble::as_tibble(cbind(rowId = newPlp,coi[,-1]))
+    newData <- dplyr::as_tibble(cbind(rowId = newPlp,coi[,-1]))
     
     # swap old covariate data with new
     plpData$covariateData$covariates <- plpData$covariateData$covariates %>% dplyr::filter(.data$covariateId != !!cId) %>% dplyr::collect()
@@ -215,7 +215,7 @@ permute <- function(plpDataLocation,cId,population){
     
     # sample the pop to replace 
     swapPlp <- sample(population$rowId,nSamp)
-    haveCidDataSwapped <- tibble::as_tibble(cbind(rowId = swapPlp,haveCidData[,-1]))
+    haveCidDataSwapped <- dplyr::as_tibble(cbind(rowId = swapPlp,haveCidData[,-1]))
     
     # find the swapped people to switch 
     connectedCovs <- plpData$covariateData$covariateRef %>% 
@@ -228,7 +228,7 @@ permute <- function(plpDataLocation,cId,population){
       dplyr::filter(.data$rowId %in% swapPlp) %>% 
       dplyr::collect()
     
-    swappedForCid <- tibble::as_tibble(cbind(rowId = haveCidData$rowId[1:nrow(plpToSwap)],plpToSwap[,-1]))
+    swappedForCid <- dplyr::as_tibble(cbind(rowId = haveCidData$rowId[1:nrow(plpToSwap)],plpToSwap[,-1]))
     
 
     # swap old covariate data with new
diff --git a/R/Predict.R b/R/Predict.R
index e84d48eec..14eff8787 100644
--- a/R/Predict.R
+++ b/R/Predict.R
@@ -168,7 +168,7 @@ applyTidyCovariateData <- function(
   
   if(!is.null(maxs)){
     if('bins'%in%colnames(maxs)){
-      covariateData$maxes <- tibble::as_tibble(maxs)  %>% dplyr::rename(covariateId = "bins") %>% 
+      covariateData$maxes <- dplyr::as_tibble(maxs)  %>% dplyr::rename(covariateId = "bins") %>% 
         dplyr::rename(maxValue = "maxs")
     } else{
       covariateData$maxes <- maxs