From 709c3a86f3ccbe6337e743736c1d8b0e2b831868 Mon Sep 17 00:00:00 2001
From: Mark Heckmann <heckmann.mark@gmail.com>
Date: Sat, 9 Jan 2021 16:04:57 +0100
Subject: [PATCH] fix docs for CRAN

---
 R/OpenRepGrid.ic.R    | 7 ++++---
 cran-comments.md      | 2 +-
 man/OpenRepGrid.ic.Rd | 5 +++--
 3 files changed, 8 insertions(+), 6 deletions(-)

diff --git a/R/OpenRepGrid.ic.R b/R/OpenRepGrid.ic.R
index aa782ce..444c58b 100644
--- a/R/OpenRepGrid.ic.R
+++ b/R/OpenRepGrid.ic.R
@@ -1,9 +1,9 @@
 
 
 #' \pkg{OpenRepGrid.ic} -  Interpretive Clustering for Repertory Grids
-#'  
+
 #' @description The \pkg{OpenRepGrid.ic} package implements \emph{Interpretive Clustering (IC)} 
-#' as outlined in \href{https://doi.org/10.1080/14780887.2020.1794088}{Burr, King, and Heckmann (2020)}. The authors describe
+#' as outlined in Burr, King, and Heckmann (2020). The authors describe
 #' a variant of construct clustering which uses a procedure from graph theory
 #' called \href{https://en.wikipedia.org/wiki/Clique_problem#Listing_all_maximal_cliques}{maximal cliques enumeration}.
 #' Given a similarity measure, in our case the number of matching scores between
@@ -16,12 +16,13 @@
 #' 
 #' The package also contains a shiny based UI you can start via the function 
 #' \code{ic()}. Visit \url{http://ic.openrepgrid.org} for an online version. 
+#' An introduction to the software is also available on \href{https://youtu.be/f9oINYA22Rc}{YouTube}.
 #' Below you find an example of how to process a repgrid in an Excel
 #' file using code only.
 #' 
 #' @references 
 #' Burr, V. King, N. & Heckmann, M. (2020) The qualitative analysis of repertory grid data: Interpretive Clustering, 
-#'     Qualitative Research in Psychology, DOI: 10.1080/14780887.2020.1794088
+#'     Qualitative Research in Psychology, \doi{10.1080/14780887.2020.1794088}
 #' @example inst/examples/01-process-excel-file.R
 #' @keywords package OpenRepGrid.ic
 #' @name OpenRepGrid.ic
diff --git a/cran-comments.md b/cran-comments.md
index 942b2d0..9effd84 100644
--- a/cran-comments.md
+++ b/cran-comments.md
@@ -1,6 +1,6 @@
 ## Submission info
 
-Several feature updates.
+Several feature updates + fixed doi link in Rd files 
 
 ## Test environments
 
diff --git a/man/OpenRepGrid.ic.Rd b/man/OpenRepGrid.ic.Rd
index 8da1467..7bc5ef9 100644
--- a/man/OpenRepGrid.ic.Rd
+++ b/man/OpenRepGrid.ic.Rd
@@ -6,7 +6,7 @@
 \title{\pkg{OpenRepGrid.ic} -  Interpretive Clustering for Repertory Grids}
 \description{
 The \pkg{OpenRepGrid.ic} package implements \emph{Interpretive Clustering (IC)} 
-as outlined in \href{https://doi.org/10.1080/14780887.2020.1794088}{Burr, King, and Heckmann (2020)}. The authors describe
+as outlined in Burr, King, and Heckmann (2020). The authors describe
 a variant of construct clustering which uses a procedure from graph theory
 called \href{https://en.wikipedia.org/wiki/Clique_problem#Listing_all_maximal_cliques}{maximal cliques enumeration}.
 Given a similarity measure, in our case the number of matching scores between
@@ -19,6 +19,7 @@ the package uses the \code{igraph} package for clique identification.
 
 The package also contains a shiny based UI you can start via the function 
 \code{ic()}. Visit \url{http://ic.openrepgrid.org} for an online version. 
+An introduction to the software is also available on \href{https://youtu.be/f9oINYA22Rc}{YouTube}.
 Below you find an example of how to process a repgrid in an Excel
 file using code only.
 }
@@ -62,7 +63,7 @@ s
 }
 \references{
 Burr, V. King, N. & Heckmann, M. (2020) The qualitative analysis of repertory grid data: Interpretive Clustering, 
-    Qualitative Research in Psychology, DOI: 10.1080/14780887.2020.1794088
+    Qualitative Research in Psychology, \doi{10.1080/14780887.2020.1794088}
 }
 \keyword{OpenRepGrid.ic}
 \keyword{package}