spelling

R/metadata.R

@@ -5,7 +5,7 @@
 #' \describe{
 #'   \item{metadata_names}{characterstrings}
 #' }
-#' @seealso \url{https://www.project-redcap.org/}
+#' @seealso project-redcap(dot)org (currently the certificate is broken)
 #' @usage data(metadata_names)
 "metadata_names"
 

inst/WORDLIST

@@ -12,12 +12,10 @@ MFI
 NA's
 OLR
 ORCID
-OpenAI's
 PASE
 REDCap
 REDCapCAST
 REDCapRITS
-RStudio
 Randomisation
 STROKEAHA
 StackOverflow
@@ -29,11 +27,10 @@ XXXX
 Zou
 agdamsbo
 al
-annonymized
+anonymized
 bstfun
 calc
 characterstrings
-chatgpt
 christophergandrud
 ci
 codecov

man/metadata_names.Rd

@@ -17,6 +17,6 @@ data(metadata_names)
 Vector of REDCap metadata headers
 }
 \seealso{
-\url{https://www.project-redcap.org/}
+project-redcap(dot)org (currently the certificate is broken)
 }
 \keyword{datasets}

vignettes/toolbox.Rmd

@@ -25,15 +25,13 @@ My own toolbox in my small workshop is a mix of some old, worn, well proven tool
 
 I have tried to collect tools and functions from other packages that I use regularly in addition to functions that I have written myself to fill use cases, that I have not been able to find solutions to elsewhere.
 
-In documenting and testing the package, I have used [OpenAI's](https://platform.openai.com/overview) chatgpt with [gpttools](https://jameshwade.github.io/gpttools/). The chatgpt is an interesting tool, that is in no way perfect, but it helps with tedious tasks. Both `gpttools` and [`gptstudio`](https://michelnivard.github.io/gptstudio/) are interesting implementations in R and RStudio.
-
 ## CPR manipulations {#cpr-intro}
 
 Note that, if handled, CPR numbers (social security numbers) should be handled with care as they a considered highly sensitive data.
 
 The CPR number is structured as _DDMMYY-XXXX_, with the 1st _X_ designating decade of birth, the last _X_ designate binary gender (not biological sex) dependent on even/uneven as female/male, and the last for digits are used in a modulus calculation to verify the validity of the CPR number. Foreigners and unidentified persons are given temporary CPR numbers including letters.
 
-More information can be found on [cpr.dk](https://cpr.dk).
+More information can be found on [cpr.dk](https://www.cpr.dk).
 
 Note, that all CPR numbers used in examples are publicly known or non-organic.
 
@@ -48,7 +46,7 @@ trunc(age)
 
 ### cpr_check()
 
-Checks validity of CPR numbers according to the [modulus 11 rule](https://cpr.dk/cpr-systemet/opbygning-af-cpr-nummeret). Note that due to limitations in the possible available CPR numbers, this rule [does not apply to all CPR numbers after 2007](https://cpr.dk/cpr-systemet/personnumre-uden-kontrolciffer-modulus-11-kontrol).
+Checks validity of CPR numbers according to the [modulus 11 rule](https://www.cpr.dk/cpr-systemet/opbygning-af-cpr-nummeret). Note that due to limitations in the possible available CPR numbers, this rule [does not apply to all CPR numbers after 2007](https://www.cpr.dk/cpr-systemet/personnumre-uden-kontrolciffer-modulus-11-kontrol).
 
 ```{r cpr_check-example}
 cpr_check(
@@ -108,7 +106,7 @@ ci_plot(
 
 ### generic_stroke()
 
-For learning purposes. Uses annonymized data from the [TALOS trial](https://doi.org/10.1161/STROKEAHA.117.020067) to output a Table 1 (with `gtsummary::tbl_summary()`), plotting the so-called grotta-bars based on mRS scores (with `rankinPlot::grottaBar()`) and a ordinal logistic regression model plot (with `stRoke::ci_plot()`).
+For learning purposes. Uses anonymized data from the [TALOS trial](https://doi.org/10.1161/STROKEAHA.117.020067) to output a Table 1 (with `gtsummary::tbl_summary()`), plotting the so-called grotta-bars based on mRS scores (with `rankinPlot::grottaBar()`) and a ordinal logistic regression model plot (with `stRoke::ci_plot()`).
 
 ```{r generic_stroke-example}
 generic_stroke(stRoke::talos,