diff --git a/.Rbuildignore b/.Rbuildignore
index b307a98..94e4933 100644
--- a/.Rbuildignore
+++ b/.Rbuildignore
@@ -22,3 +22,4 @@ $run_dev.*
 ^.lintr$
 ^cran-comments\.md$
 ^CITATION\.cff$
+^CRAN-SUBMISSION$
diff --git a/CITATION.cff b/CITATION.cff
index f843bbd..c20a53f 100644
--- a/CITATION.cff
+++ b/CITATION.cff
@@ -8,11 +8,11 @@ message: 'To cite package "ordinalsimr" in publications use:'
 type: software
 license: MIT
 title: 'ordinalsimr: Compare Ordinal Endpoints Using Simulations'
-version: 0.1.1
+version: 0.1.3
 doi: 10.5281/zenodo.14697216
 abstract: Simultaneously evaluate multiple ordinal outcome measures. Applied data
   analysts in particular are faced with uncertainty in choosing appropriate statistical
-  tests for ordinal data. The included Shiny applications allows users to simulate
+  tests for ordinal data. The included 'shiny' application allows users to simulate
   outcomes given different ordinal data distributions.
 authors:
 - family-names: Callahan
@@ -35,7 +35,7 @@ preferred-citation:
   copyright: MIT
   abstract: Simultaneously evaluate multiple ordinal outcome measures. Applied data
     analysts in particular are faced with uncertainty in choosing appropriate statistical
-    tests for ordinal data. The included Shiny applications allows users to simulate
+    tests for ordinal data. The included 'shiny' applications allows users to simulate
     outcomes given different ordinal data distributions.
 repository-code: https://github.com/NeuroShepherd/ordinalsimr
 url: https://neuroshepherd.github.io/ordinalsimr/
diff --git a/DESCRIPTION b/DESCRIPTION
index 71949c9..ff2ae2e 100644
--- a/DESCRIPTION
+++ b/DESCRIPTION
@@ -1,13 +1,13 @@
 Package: ordinalsimr
 Title: Compare Ordinal Endpoints Using Simulations
-Version: 0.1.1
+Version: 0.1.3
 Authors@R: 
     person(given = "Pat",
            family = "Callahan",
            role = c("aut", "cre", "cph"),
            email = "patricktcallahan18@gmail.com",
            comment = c(ORCID = "0000-0003-1769-7580"))
-Description: Simultaneously evaluate multiple ordinal outcome measures. Applied data analysts in particular are faced with uncertainty in choosing appropriate statistical tests for ordinal data. The included Shiny applications allows users to simulate outcomes given different ordinal data distributions.
+Description: Simultaneously evaluate multiple ordinal outcome measures. Applied data analysts in particular are faced with uncertainty in choosing appropriate statistical tests for ordinal data. The included 'shiny' application allows users to simulate outcomes given different ordinal data distributions.
 License: MIT + file LICENSE
 Imports: 
     assertthat,
diff --git a/NEWS.md b/NEWS.md
index 7bf2a47..229142c 100644
--- a/NEWS.md
+++ b/NEWS.md
@@ -1,3 +1,7 @@
+# ordinalsimr 0.1.3
+
+* Updates to match CRAN submission standards
+
 # ordinalsimr 0.1.1
 
 * Create DOI via Zenodo and add to CITATION file
diff --git a/R/run_app.R b/R/run_app.R
index 383ea60..44010ff 100644
--- a/R/run_app.R
+++ b/R/run_app.R
@@ -4,6 +4,8 @@
 #' See `?golem::get_golem_options` for more details.
 #' @inheritParams shiny::shinyApp
 #'
+#' @return NULL, the function is called for its side effects
+#'
 #' @export
 #' @importFrom shiny shinyApp
 #' @importFrom golem with_golem_options
diff --git a/R/run_simulations.R b/R/run_simulations.R
index 77bbd68..1163ccd 100644
--- a/R/run_simulations.R
+++ b/R/run_simulations.R
@@ -22,7 +22,7 @@
 #'   sample_prob = c(0.5, 0.5),
 #'   prob0 = c(0.1, 0.2, 0.3, 0.4),
 #'   prob1 = c(0.6, 0.2, 0.1, 0.1),
-#'   niter = 50
+#'   niter = 40
 #' )
 #'
 run_simulations <- function(sample_size, sample_prob, prob0, prob1, niter, included = "all",
diff --git a/cran-comments.md b/cran-comments.md
index 8345602..9584149 100644
--- a/cran-comments.md
+++ b/cran-comments.md
@@ -1,6 +1,11 @@
-## R CMD check results
+## Resubmission -- 0.1.3
 
-0 errors | 0 warnings | 1 note
+This is a resubmission. In this version I have:
+
+* Reformatted the DESCRIPTION file to follow the CRAN guidelines for writing package names.
+* Updated code in the `ordinalsimr-options` vignette to reset the options to their default values after the vignette is run.
+* Reduced the number of simulation iterations from 50 to 40 in the example for `run_simulations.R` to keep the run time for examples under 5s. Previously, the example took 5.019s to run on r-devel-linux-x86_64-debian-gcc.
+* A @return tag was added to the `run_app` function in the `run_app.R` file, and indicates the function is called for its side-effects
+
+Additionally, we are currently working on a manuscript that will be added to the DESCRIPTION and CITATION files in a later release.
 
-* This is a new release.
-* This package imports the {rms} package which depends on R (>= 4.4.0).
diff --git a/inst/CITATION b/inst/CITATION
index 5797cdf..620655c 100644
--- a/inst/CITATION
+++ b/inst/CITATION
@@ -19,7 +19,7 @@ bibentry(
   urldate = "2025-01-19",
   copyright = "MIT",
   date = "2025-01",
-  abstract = "Simultaneously evaluate multiple ordinal outcome measures. Applied data analysts in particular are faced with uncertainty in choosing appropriate statistical tests for ordinal data. The included Shiny applications allows users to simulate outcomes given different ordinal data distributions."
+  abstract = "Simultaneously evaluate multiple ordinal outcome measures. Applied data analysts in particular are faced with uncertainty in choosing appropriate statistical tests for ordinal data. The included 'shiny' applications allows users to simulate outcomes given different ordinal data distributions."
 )
 
 
diff --git a/man/ordinalsimr-package.Rd b/man/ordinalsimr-package.Rd
index dd6b42f..e2e16bf 100644
--- a/man/ordinalsimr-package.Rd
+++ b/man/ordinalsimr-package.Rd
@@ -6,7 +6,7 @@
 \alias{ordinalsimr-package}
 \title{ordinalsimr: Compare Ordinal Endpoints Using Simulations}
 \description{
-Simultaneously evaluate multiple ordinal outcome measures. Applied data analysts in particular are faced with uncertainty in choosing appropriate statistical tests for ordinal data. The included Shiny applications allows users to simulate outcomes given different ordinal data distributions.
+Simultaneously evaluate multiple ordinal outcome measures. Applied data analysts in particular are faced with uncertainty in choosing appropriate statistical tests for ordinal data. The included 'shiny' application allows users to simulate outcomes given different ordinal data distributions.
 }
 \seealso{
 Useful links:
diff --git a/man/run_app.Rd b/man/run_app.Rd
index c6c36f7..ea15a98 100644
--- a/man/run_app.Rd
+++ b/man/run_app.Rd
@@ -36,6 +36,9 @@ expression in order for the match to be considered successful.}
 \item{...}{arguments to pass to golem_opts.
 See `?golem::get_golem_options` for more details.}
 }
+\value{
+NULL, the function is called for its side effects
+}
 \description{
 Run the Shiny Application
 }
diff --git a/man/run_simulations.Rd b/man/run_simulations.Rd
index 85fd212..ce8cb4c 100644
--- a/man/run_simulations.Rd
+++ b/man/run_simulations.Rd
@@ -47,7 +47,7 @@ run_simulations(
   sample_prob = c(0.5, 0.5),
   prob0 = c(0.1, 0.2, 0.3, 0.4),
   prob1 = c(0.6, 0.2, 0.1, 0.1),
-  niter = 50
+  niter = 40
 )
 
 }
diff --git a/vignettes/ordinalsimr-options.Rmd b/vignettes/ordinalsimr-options.Rmd
index ff7d283..1472b3b 100644
--- a/vignettes/ordinalsimr-options.Rmd
+++ b/vignettes/ordinalsimr-options.Rmd
@@ -12,6 +12,8 @@ knitr::opts_chunk$set(
   collapse = TRUE,
   comment = "#>"
 )
+
+start_options <- options()
 ```
 
 ```{r setup}
@@ -101,6 +103,9 @@ get_ordinalsimr_options()
 
 
 
+```{r, include = FALSE}
+options(start_options)
+```