diff --git a/R/encoding.R b/R/encoding.R
index 5328491..34138b5 100644
--- a/R/encoding.R
+++ b/R/encoding.R
@@ -53,6 +53,8 @@ dummyCode <- function(df, vars) {
 #' result$randPars
 #' head(result$X)
 recodeData <- function(data, pars, randPars) {
+  data <- as.data.frame(data) # tibbles break things
+  factorLevels <- getFactorLevels(data, pars) # need to store for predicting
   data <- orderedFactorsToChars(data) # ordered factors cause weird names
   formula <- stats::as.formula(paste0("~ ", paste(pars, collapse = " + ")))
   X <- getDesignMatrix(formula, data)
@@ -60,6 +62,7 @@ recodeData <- function(data, pars, randPars) {
     formula = formula,
     X = X,
     pars = colnames(X),
+    factorLevels = factorLevels,
     randPars = recodeRandPars(data, pars, randPars)
   ))
 }
diff --git a/R/modelInputs.R b/R/modelInputs.R
index cd571ee..2d9e51a 100644
--- a/R/modelInputs.R
+++ b/R/modelInputs.R
@@ -50,12 +50,12 @@ getModelInputs <- function(
   # Get the design matrix, recoding parameters that are categorical
   # or have interactions
   data <- as.data.frame(data) # tibbles break things
-  factorLevels <- getFactorLevels(data, pars) # need to store for predicting
   recoded <- recodeData(data, pars, randPars)
   formula <- recoded$formula
   X <- recoded$X
   pars <- recoded$pars
   randPars <- recoded$randPars
+  factorLevels <- recoded$factorLevels
   scalePar <- defineScalePar(data, inputs, modelSpace)
   outcome <- as.matrix(data[outcome])