diff --git a/DESCRIPTION b/DESCRIPTION
index e980f83..af5ce08 100644
--- a/DESCRIPTION
+++ b/DESCRIPTION
@@ -1,7 +1,7 @@
 Package: singleRcapture
 Type: Package
 Title: Single-Source Capture-Recapture Models
-Version: 0.2.1.1
+Version: 0.2.1.2
 Authors@R:
     c(person(given = "Piotr",
              family = "Chlebicki",
diff --git a/R/Internals.R b/R/Internals.R
index 65560aa..3edfd95 100644
--- a/R/Internals.R
+++ b/R/Internals.R
@@ -492,12 +492,6 @@ singleRcaptureinternalIRLSmultipar <- function(dependent,
 # make Xvlm matrix
 #' @importFrom stats terms
 singleRinternalGetXvlmMatrix <- function(X, formulas, parNames, contrasts = NULL) {
-  if (length(formulas[[1]]) == 3) {
-    #formulas[[1]][[2]] <- NULL
-  }
-  if (attr(attr(X, "terms"), "response") != 0) {
-    #X <- X[, colnames(X)[-attr(attr(X, "terms"), "response")], drop = FALSE]
-  }
   nPar <- length(parNames)
   Xses <- list()
   
@@ -506,13 +500,12 @@ singleRinternalGetXvlmMatrix <- function(X, formulas, parNames, contrasts = NULL
     if (length(attr(terms(formulas[[k]], data = X), "term.labels")) != 0) {
       Xses[[k]] <- model.matrix(
         terms(formulas[[k]], data = X),
-        data = X[, colnames(X)]
+        data = X
       )
     } else {
       Xses[[k]] <- model.matrix(
         ~ 1,
-        X[, intersect(attr(terms(formulas[[k]], data = X), "term.labels"),
-                      colnames(X)), drop = FALSE]
+        X
       )
       if (attr(terms(formulas[[k]], data = X), "intercept") == 0)
         warning(paste0(
diff --git a/R/sandwichMethods.R b/R/sandwichMethods.R
index 6722d60..8a80da0 100644
--- a/R/sandwichMethods.R
+++ b/R/sandwichMethods.R
@@ -50,7 +50,7 @@ bread.singleRStaticCountData <- function(x,...) {
 #' @author Piotr Chlebicki, Maciej Beręsewicz
 #' 
 #' @description S3 method for \code{vcovHC} to handle \code{singleRStaticCountData} class objects. 
-#' Works exactly like \code{vcov.default} the only difference being that this method handles vector generalised linear models.
+#' Works exactly like \code{vcovHC.default} the only difference being that this method handles vector generalised linear models.
 #' Updating the covariance matrix in variance/standard error estimation for population size estimator can be done via [singleRcapture::redoPopEstimation()]
 #'
 #' @param x a fitted \code{singleRStaticCountData} class object.