diff --git a/DESCRIPTION b/DESCRIPTION
index d99a81c..ad71d9c 100644
--- a/DESCRIPTION
+++ b/DESCRIPTION
@@ -1,11 +1,11 @@
 Package: lsasim
-Title: Simulate Large Scale Assessment Data
-Version: 1.0.1.9000
+Title: Functions to Facilitate the Simulation of Large Scale Assessment Data
+Version: 1.0.1
 Authors@R: c(
   person("Tyler", "Matta", email = "tyler.matta@gmail.com", role = c("aut", "cre")),
-  person("Yuan-Ling Linda", "Liaw", email = "linda08@uw.edu", role = "ctb"),
-  person("Leslie", "Rutkowski", email = "leslie.rutkowski@cemo.uio.no", role = "ctb"),
-  person("David", "Rutkowski", email = "david.rutkowski@cemo.uio.no", role = "ctb"),
+  person("Leslie", "Rutkowski", email = "leslie.rutkowski@cemo.uio.no", role = "aut"),
+  person("David", "Rutkowski", email = "david.rutkowski@cemo.uio.no", role = "aut"),
+  person("Yuan-Ling Linda", "Liaw", email = "linda08@uw.edu", role = "aut"),
   person("Kondwani Kajera", "Mughogho", email = "k.k.mughogho@cemo.uio.no", role = "ctb")
   )
 BugReports: https://github.com/tmatta/lsasim/issues
@@ -17,4 +17,4 @@ Depends:
 License: GPL-3
 Encoding: UTF-8
 LazyData: true
-RoxygenNote: 5.0.1
+RoxygenNote: 6.0.1
diff --git a/NEWS.md b/NEWS.md
index ec0ac88..0a16835 100644
--- a/NEWS.md
+++ b/NEWS.md
@@ -1,4 +1,4 @@
-lsasim 1.0.2.9000
+lsasim 1.0.1
 -------------
 
 ### API changes
diff --git a/R/cor_gen.R b/R/cor_gen.R
index 48521b1..4b8877b 100644
--- a/R/cor_gen.R
+++ b/R/cor_gen.R
@@ -3,6 +3,7 @@
 #' Creates a random correlation matrix.  
 #'
 #' @param n_var integer number of variables.
+#' @param cov_bounds a vector containing the bounds of the covariance matrix.
 #' 
 #' @section Details:
 #' The result from \code{cor_gen} can be used directly with the \code{cor_matrix}
diff --git a/man/block_design.Rd b/man/block_design.Rd
index 98ed857..55223a8 100644
--- a/man/block_design.Rd
+++ b/man/block_design.Rd
@@ -30,6 +30,7 @@ represent the total number of items. \code{item_block_matrix[1, 1] = 1} indicate
 that block 1 contains item 1 while \code{item_block_matrix[1, 2] = 0} indicates that
 block 2 does not contain item 1.
 }
+
 \examples{
 item_param <- data.frame(item = seq(1:25), b = runif(25, -2, 2))
 ib_matrix <- matrix(nrow = 25, ncol = 5, byrow = FALSE, 
@@ -42,4 +43,3 @@ block_design(n_blocks = 5, item_parameters = item_param, item_block_matrix = ib_
 block_design(n_blocks = 5, item_parameters = item_param)
 
 }
-
diff --git a/man/booklet_design.Rd b/man/booklet_design.Rd
index dabc605..19716bf 100644
--- a/man/booklet_design.Rd
+++ b/man/booklet_design.Rd
@@ -32,6 +32,7 @@ The default \code{book_design} assigns two blocks to every booklet in a spiral d
 The number of default booklets is equal to the number of blocks and must be >= 3. 
 If \code{ncol(item_block_assignment)} < 3, \code{book_design} must be specified.
 }
+
 \examples{
 i_blk_mat <- matrix(seq(1:40), ncol = 5) 
 blk_book <- matrix(c(1, 0, 1, 0, 0, 0, 1, 0, 1, 0, 0, 0, 1, 0, 1,
@@ -41,4 +42,3 @@ booklet_design(item_block_assignment = i_blk_mat, book_design = blk_book)
 booklet_design(item_block_assignment = i_blk_mat)
 
 }
-
diff --git a/man/booklet_sample.Rd b/man/booklet_sample.Rd
index 0ef7137..2e5ec37 100644
--- a/man/booklet_sample.Rd
+++ b/man/booklet_sample.Rd
@@ -32,10 +32,10 @@ the difference between the most sampled and least sampled booklets.}
 If using \code{booklet_sample} in tandem with \code{booklet_design}, \code{book_item_design}
 is the the first element of the returned list of \code{block_design}.
 }
+
 \examples{
 it_bk <- matrix(c(1, 2, 1, 4, 5, 4, 7, 8, 7, 10, 3, 10, 2, 6, 3, 5, 9, 6, 8, 0, 9), 
            ncol = 3, byrow = TRUE)
 booklet_sample(n_subj = 10, book_item_design = it_bk, book_prob = c(.2, .5, .3))
 
 }
-
diff --git a/man/cor_gen.Rd b/man/cor_gen.Rd
index 47835aa..03d0127 100644
--- a/man/cor_gen.Rd
+++ b/man/cor_gen.Rd
@@ -4,10 +4,12 @@
 \alias{cor_gen}
 \title{Generation of random correlation matrix}
 \usage{
-cor_gen(n_var)
+cor_gen(n_var, cov_bounds = c(-1, 1))
 }
 \arguments{
 \item{n_var}{integer number of variables.}
+
+\item{cov_bounds}{a vector containing the bounds of the covariance matrix.}
 }
 \description{
 Creates a random correlation matrix.
@@ -17,8 +19,8 @@ Creates a random correlation matrix.
 The result from \code{cor_gen} can be used directly with the \code{cor_matrix}
 argument of \code{questionnaire_gen}.
 }
+
 \examples{
 cor_gen(n_var = 10)
 
 }
-
diff --git a/man/irt_gen.Rd b/man/irt_gen.Rd
index 7e540a1..8fc5b35 100644
--- a/man/irt_gen.Rd
+++ b/man/irt_gen.Rd
@@ -26,4 +26,3 @@ irt_gen(theta = 0.2, a_par = 1.15, b_par = 0.6)
 irt_gen(theta = 0.2, a_par = 1.15, b_par = 0.6, c_par = 0.2)
 
 }
-
diff --git a/man/item_gen.Rd b/man/item_gen.Rd
index 1b4e865..cc82a37 100644
--- a/man/item_gen.Rd
+++ b/man/item_gen.Rd
@@ -33,6 +33,7 @@ Creates a data frame of item parameters.
 The data frame includes two variables \code{p} and \code{k} which indicate the 
 number of parameters and the number of thresholds, respectively
 }
+
 \examples{
 item_gen(b_bounds = c(-2, 2), a_bounds = c(.75, 1.25), 
   thresholds = c(1, 2, 3), n_1pl = c(5, 5, 5), n_2pl = c(0, 0, 5))
@@ -40,4 +41,3 @@ item_gen(b_bounds = c(-2, 2), a_bounds = c(.75, 1.25), c_bounds = c(0, .25),
   n_2pl = 5, n_3pl = 5)
 
 }
-
diff --git a/man/pisa2012_math_block.Rd b/man/pisa2012_math_block.Rd
index bcc1042..836c56f 100644
--- a/man/pisa2012_math_block.Rd
+++ b/man/pisa2012_math_block.Rd
@@ -33,4 +33,3 @@ A dataset containing indicators associating those PISA 2012 mathematics items
 to the PISA 2012 mathematics item blocks.
 }
 \keyword{datasets}
-
diff --git a/man/pisa2012_math_booklet.Rd b/man/pisa2012_math_booklet.Rd
index 75b08d2..0a86988 100644
--- a/man/pisa2012_math_booklet.Rd
+++ b/man/pisa2012_math_booklet.Rd
@@ -31,4 +31,3 @@ A dataset containing indicators associating those PISA 2012 mathematics item
 blocks to the PISA 2012 mathematics standard test booklet set.
 }
 \keyword{datasets}
-
diff --git a/man/pisa2012_math_item.Rd b/man/pisa2012_math_item.Rd
index 1508c7c..00e99af 100644
--- a/man/pisa2012_math_item.Rd
+++ b/man/pisa2012_math_item.Rd
@@ -26,4 +26,3 @@ A dataset containing the estimated item parameters for the PISA 2012
 mathematics assessment.
 }
 \keyword{datasets}
-
diff --git a/man/pisa2012_q_cormat.Rd b/man/pisa2012_q_cormat.Rd
index a01f57f..30e2a7e 100644
--- a/man/pisa2012_q_cormat.Rd
+++ b/man/pisa2012_q_cormat.Rd
@@ -52,5 +52,5 @@ ordinal variables.
 
 These data are for illustration purposes only.  Handling of missing data may not be suitable for valid inferences.
 }
-\keyword{datasets}
 
+\keyword{datasets}
diff --git a/man/pisa2012_q_marginal.Rd b/man/pisa2012_q_marginal.Rd
index fe1a096..f9b0294 100644
--- a/man/pisa2012_q_marginal.Rd
+++ b/man/pisa2012_q_marginal.Rd
@@ -51,5 +51,5 @@ Element 19 is the marginal proportion for the selected mathematics plausible val
 
 These data are for illustration purposes only.  Handling of missing data may not be suitable for valid inferences.
 }
-\keyword{datasets}
 
+\keyword{datasets}
diff --git a/man/proportion_gen.Rd b/man/proportion_gen.Rd
index 728e82f..2a405d1 100644
--- a/man/proportion_gen.Rd
+++ b/man/proportion_gen.Rd
@@ -24,9 +24,9 @@ proportions of a discrete variable.
 The result from \code{proportion_gen} can be used directly with the \code{cat_prop}
 argument of \code{questionnaire_gen}.
 }
+
 \examples{
 proportion_gen(cat_options = c(1, 2, 3), n_cat_options = c(2, 2, 2))
 proportion_gen(cat_options = c(1, 3), n_cat_options = c(4, 5))
 
 }
-
diff --git a/man/questionnaire_gen.Rd b/man/questionnaire_gen.Rd
index efcab55..629d975 100644
--- a/man/questionnaire_gen.Rd
+++ b/man/questionnaire_gen.Rd
@@ -47,10 +47,10 @@ If \code{cat_prop} is a named list, those names will be used as variable names
 for the returned \code{data.frame}.  Generic names will be provided to the 
 variables if \code{cat_prop} is not named.
 }
+
 \examples{
 questionnaire_gen(n = 10, cat_prop = list(c(1), c(.25, .6, 1)), 
                   cor_matrix = matrix(c(1, .6, .6, 1), nrow = 2), 
                   c_mean = 2, c_sd = 1.5, theta = TRUE)
 
 }
-
diff --git a/man/response_gen.Rd b/man/response_gen.Rd
index f5178d1..519b331 100644
--- a/man/response_gen.Rd
+++ b/man/response_gen.Rd
@@ -35,6 +35,7 @@ Creates a data frame of discrete item responses based on.
 
 Generalized partial credit models (\code{!is.null(d_par)}) uses threshold parameterization.
 }
+
 \examples{
 set.seed(1234)
 s_id <- c(1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 2, 2, 3, 3, 3, 3, 3, 3, 3, 4, 4, 
@@ -59,4 +60,3 @@ response_gen(subject = s_id, item = i_id, theta = rnorm(20, 0, 1),
              b_par = bb, a_par = aa, c_par = cc, d_par = dd)
 
 }
-