fix: urls

- urlchecker indicates problems with redirection
- one url was not fixable, it was "unurled"

README.Rmd

@@ -73,7 +73,7 @@ Sounds interesting? Then check out some introductory literature such as @furr200
 
 Cofad has two components, the plain R package and a shiny-app that offers an intuitive graphical user interface.
 
-If you just want to use the cofad-app, you do not need to install it. Just go to https://cofad.titz.science and use it there. An example data file is loaded when you go to https://cofad.titz.science/example.
+If you just want to use the cofad-app, you do not need to install it. Just go to https://cofad.titz.science and use it there. An example data file is loaded when you add /example after the url.
 
 If you prefer the command line interface or want to use the cofad-app locally, install it from github (you need the package devtools for this):
 
@@ -102,7 +102,7 @@ Before we start: Your data has to be in the long-format (also referred to as nar
 
 The graphical-user-interface is self-explanatory. Just load your data and drag the variables to the correct position. At the moment you can only read .sav (SPSS) and .csv files.
 
-As an example go to https://cofad.titz.science/example which will load a data set from @rosenthal2000 (Table 5.3). The cognitive ability of nine children belonging to different age groups (between) was measured four times (within).
+As an example go to `https://cofad.titz.science/example` which will load a data set from @rosenthal2000 (Table 5.3). The cognitive ability of nine children belonging to different age groups (between) was measured four times (within).
 
 There are two hypotheses:
 
@@ -387,7 +387,7 @@ If you need answers on how to use the package, drop an e-mail at johannes at tit
 
 Comments and feedback of any kind are very welcome! We will thoroughly consider every suggestion on how to improve the code, the documentation, and the presented examples. Even minor things, such as suggestions for better wording or improving grammar in any part of the package, are more than welcome.
 
-If you want to make a pull request, please check that you can still build the package without any errors, warnings, or notes. Overall, simply stick to the R packages book: https://r-pkgs.org/ and follow the code style described here: http://r-pkgs.had.co.nz/r.html#style
+If you want to make a pull request, please check that you can still build the package without any errors, warnings, or notes. Overall, simply stick to the R packages book: https://r-pkgs.org/ and follow the code style described here: https://style.tidyverse.org/
 
 ## Acknowledgments
 

README.md

@@ -69,7 +69,7 @@ offers an intuitive graphical user interface.
 
 If you just want to use the cofad-app, you do not need to install it.
 Just go to <https://cofad.titz.science> and use it there. An example
-data file is loaded when you go to <https://cofad.titz.science/example>.
+data file is loaded when you add /example after the url.
 
 If you prefer the command line interface or want to use the cofad-app
 locally, install it from github (you need the package devtools for
@@ -111,7 +111,7 @@ The graphical-user-interface is self-explanatory. Just load your data
 and drag the variables to the correct position. At the moment you can
 only read .sav (SPSS) and .csv files.
 
-As an example go to <https://cofad.titz.science/example> which will load
+As an example go to `https://cofad.titz.science/example` which will load
 a data set from Rosenthal et al. (2000) (Table 5.3). The cognitive
 ability of nine children belonging to different age groups (between) was
 measured four times (within).
@@ -277,7 +277,7 @@ ca <- calc_contrast(dv = empathy, between = major,
                     data = furr_p4)
 ca
 #> 
-#> We ran a contrast analysis for the following between contrasts: business = -1; chemistry = -1; education = 1; psychology = 1. This resulted in statistics of F(1,16) = 57.778; p = 0.00000107 and an effect magnitude of r_effectsize = 0.847.
+#> We ran a contrast analysis for the following between contrasts: business = -1; chemistry = -1; education = 1; psychology = 1. This resulted in statistics of F(1,16) = 57.778; p = 1.07e-06 and an effect magnitude of r_effectsize = 0.847.
 ```
 
 When you compare the numbers to the ones presented in Furr (2004), you
@@ -304,7 +304,7 @@ ca <- calc_contrast(dv = empathy, between = major,
 ``` r
 ca
 #> 
-#> We ran a contrast analysis for the following between contrasts: business = -4.75; chemistry = -17.75; education = 5.25; psychology = 17.25. This resulted in statistics of F(1,16) = 37.466; p = 0.00001475 and an effect magnitude of r_effectsize = 0.682.
+#> We ran a contrast analysis for the following between contrasts: business = -4.75; chemistry = -17.75; education = 5.25; psychology = 17.25. This resulted in statistics of F(1,16) = 37.466; p = 1.475e-05 and an effect magnitude of r_effectsize = 0.682.
 ```
 
 The manual test gives the same effect size:
@@ -757,7 +757,7 @@ than welcome.
 If you want to make a pull request, please check that you can still
 build the package without any errors, warnings, or notes. Overall,
 simply stick to the R packages book: <https://r-pkgs.org/> and follow
-the code style described here: <http://r-pkgs.had.co.nz/r.html#style>
+the code style described here: <https://style.tidyverse.org/>
 
 ## Acknowledgments