fixing broken links #666

.Rbuildignore

@@ -13,3 +13,4 @@
 ^\.github$
 ^pkgdown$
 ^Makefile$
+^CRAN-SUBMISSION$

Makefile

@@ -3,6 +3,7 @@ test:
 
 check:
 	Rscript -e "devtools::check()"
+	Rscript -e "urlchecker::url_check()"
 
 build_site:
 	Rscript -e "pkgdown::build_site()"

R/surv_pvalue.R

@@ -23,7 +23,7 @@ NULL
 #'  .... Case insensitive partial match is allowed.\cr\cr To learn more about
 #'  the mathematical background behind the different log-rank weights, read the
 #'  following blog post on R-Addict:
-#'  \href{http://r-addict.com/2017/02/09/Fancy-Survival-Plots.html}{Comparing
+#'  \href{https://rpkgs.datanovia.com/survminer/articles/Specifiying_weights_in_log-rank_comparisons.html}{Comparing
 #'  (Fancy) Survival Curves with Weighted Log-rank Tests}
 #'@param test.for.trend logical value. Default is FALSE. If TRUE, returns the
 #'  test for trend p-values. Tests for trend are designed to detect ordered

cran-comments.md

@@ -15,6 +15,12 @@ All packages that I could install passed.
 
 This is an update version 0.5.0 (see NEWS.md)
 
+## Resubmission
+
+This is a resubmission. In this version I have:
+
+- Updated broken URLs found in inst/doc/Informative_Survival_Plots.html and man/surv_pvalue.Rd
+
 
 
 

vignettes/Informative_Survival_Plots.Rmd

@@ -33,10 +33,10 @@ opts_chunk$set(
 
 # Motivation
 
-[Hadley Wickham's ggplot2 version 2.0 revolution](https://www.r-bloggers.com/2015/12/ggplot-2-0-0/), at the end of 2015, triggered many crashes in dependent R packages, that finally led to deletions of few packages from [The Comprehensive R Archive Network](https://cran.r-project.org/). It occured that `survMisc` package was removed from CRAN on 27th of January 2016 and R world remained helpless in the struggle with the elegant visualizations of survival analysis. Then a new tool - [survminer](https://cran.r-project.org/package=survminer) package, created by [Alboukadel Kassambara](https://github.com/kassambara) - appeared on the R survival scene to fill the gap in visualizing the Kaplan-Meier estimates of survival curves in elegant grammar of graphics like way. This blog presents main features of core `ggsurvplot()` function from survminer package, *which creates the most informative, elegant and flexible survival plots that I have seen!*
+Hadley Wickham's ggplot2 version 2.0 revolution, at the end of 2015, triggered many crashes in dependent R packages, that finally led to deletions of few packages from [The Comprehensive R Archive Network](https://cran.r-project.org/). It occured that `survMisc` package was removed from CRAN on 27th of January 2016 and R world remained helpless in the struggle with the elegant visualizations of survival analysis. Then a new tool - [survminer](https://cran.r-project.org/package=survminer) package, created by [Alboukadel Kassambara](https://github.com/kassambara) - appeared on the R survival scene to fill the gap in visualizing the Kaplan-Meier estimates of survival curves in elegant grammar of graphics like way. This blog presents main features of core `ggsurvplot()` function from survminer package, *which creates the most informative, elegant and flexible survival plots that I have seen!*
 
 
-During the development of [RTCGA](http://rtcga.github.io/RTCGA/) package (about which I wrote [here](http://r-addict.com/2016/05/04/RTCGA-Quick-Guide.html)) we encountered a need to provide the simplest possible interface to estimates of survival curves for biotechnologists and [the discovery of `ggsurvplot()`](http://www.sthda.com/english/wiki/survminer-r-package-survival-data-analysis-and-visualization) was a bull's-eye! [Many have tried](https://github.com/tidyverse/ggplot2/issues/1080) to provide a package or function for ggplot2-like plots that would present the basic tool of survival analysis: Kaplan-Meier estimates of survival curves, but none of earlier attempts have provided such a rich structure of features and flexibility as survminer. 
+During the development of [RTCGA](http://rtcga.github.io/RTCGA/) package there was a need to provide the simplest possible interface to estimates of survival curves for biotechnologists and [the discovery of `ggsurvplot()`](http://www.sthda.com/english/wiki/survminer-r-package-survival-data-analysis-and-visualization) was a bull's-eye! [Many have tried](https://github.com/tidyverse/ggplot2/issues/1080) to provide a package or function for ggplot2-like plots that would present the basic tool of survival analysis: Kaplan-Meier estimates of survival curves, but none of earlier attempts have provided such a rich structure of features and flexibility as survminer. 
 On basis of estimates of survival curves one can infere on differences in survival times between compared groups, so survival plots are very useful and can be seen in almost every publication in the field of survival analysis and time to event models. 
 
 # Example