chore: update md

README.Rmd

@@ -77,7 +77,7 @@ If you just want to use the cofad-app, you do not need to install it. Just go to
 
 If you prefer the command line interface or want to use the cofad-app locally, install it from CRAN:
 
-```{r}
+```{r message=FALSE}
 install.packages("cofad")
 ```
 

README.md

@@ -76,8 +76,6 @@ locally, install it from CRAN:
 
 ``` r
 install.packages("cofad")
-#> Installing package into '/tmp/Rtmpl1xjgl/temp_libpath342fc6426ca78'
-#> (as 'lib' is unspecified)
 ```
 
 Alternatively, you can also install the development version from github
@@ -96,7 +94,7 @@ You can also run the app:
 cofad::run_app()
 ```
 
-<!-- If you have any problems installing cofad, check that your R version is up to date (currently R version 4.4.1 (2024-06-14)). If you are using Windows, enable TLS 1.2 in the Internet Options Advanced tab (see https://github.com/r-lib/remotes/issues/130#issuecomment-423830669). Under Windows, you will also need Rtools to build the package: https://cran.r-project.org/bin/windows/Rtools/. -->
+<!-- If you have any problems installing cofad, check that your R version is up to date (currently R version 4.4.2 (2024-10-31)). If you are using Windows, enable TLS 1.2 in the Internet Options Advanced tab (see https://github.com/r-lib/remotes/issues/130#issuecomment-423830669). Under Windows, you will also need Rtools to build the package: https://cran.r-project.org/bin/windows/Rtools/. -->
 <!-- If it still does not work drop an e-mail at johannes at titz.science or at johannes.titz at gmail.com. -->
 
 ## Using cofad
@@ -269,9 +267,6 @@ ca <- calc_contrast(dv = empathy, between = major,
 ca
 #> 
 #> We ran a contrast analysis for the following between contrasts: business = 1; chemistry = -1; education = 0; psychology = 0. This resulted in statistics of F(1,16) = 0.684; p = 0.4205 and an effect magnitude of r_effectsize = 0.092.
-```
-
-``` r
 ca <- calc_contrast(dv = empathy, between = major,
                     lambda_between = c("psychology" = 1, "education" = 1,
                                        "business" = -1, "chemistry" = -1),
@@ -300,9 +295,6 @@ ca <- calc_contrast(dv = empathy, between = major,
                                        "business" = 51, "chemistry" = 38),
                     data = furr_p4)
 #> lambdas are centered and rounded to 3 digits
-```
-
-``` 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 = 1.475e-05 and an effect magnitude of r_effectsize = 0.682.
@@ -339,9 +331,6 @@ head(sedlmeier_p537)
 #> 4           29           4 without music
 #> 5           30           5 without music
 #> 6           33           6 without music
-```
-
-``` r
 within <- calc_contrast(dv = reading_test, within = music,
                         lambda_within = c("without music" = 1.25, 
                                           "white noise" = 0.25,
@@ -365,9 +354,6 @@ summary(within)
 #>                 
 #> r-contrast 0.687
 #> g-contrast 1.863
-```
-
-``` r
 within
 #> 
 #> We ran a contrast analysis for the following within contrasts: classic = -0.75; jazz = -0.75; white noise = 0.25; without music = 1.25. This resulted in statistics of t(7) = 5.269; p = 0.000581 and an effect magnitude of g_effectsize = 1.863.
@@ -434,9 +420,6 @@ head(rosenthal_tbl53)
 #> 4  4   age10  4      1
 #> 5  5   age10  5      1
 #> 6  5   age10  6      1
-```
-
-``` r
 lambda_within <- c("1" = -3, "2" = -1, "3" = 1, "4" = 3)
 lambda_between <-c("age8" = -1, "age10" = 0, "age12" = 1)
 
@@ -542,9 +525,6 @@ ca_competing <- calc_contrast(
   data = sedlmeier_p525
 )
 #> lambdas are centered and rounded to 3 digits
-```
-
-``` r
 summary(ca_competing)
 #> Contrast Analysis Between
 #> 
@@ -569,9 +549,6 @@ summary(ca_competing)
 #> r_effectsize   0.264
 #> r_contrast     0.312
 #> r_alerting     0.445
-```
-
-``` r
 ca_competing
 #> 
 #> We ran a contrast analysis for the following between contrasts: JT = 0.68; KT = 0.49; MT = -1.17. This resulted in statistics of F(1,12) = 1.291; p = 0.278 and an effect magnitude of r_effectsize = 0.264.
@@ -659,9 +636,6 @@ contr_wi <- calc_contrast(
   data = sedlmeier_p537
 )
 #> lambdas are centered and rounded to 3 digits
-```
-
-``` r
 summary(contr_wi)
 #> Contrast Analysis Within
 #> 
@@ -681,9 +655,6 @@ summary(contr_wi)
 #>                  
 #> r-contrast -0.561
 #> g-contrast -1.333
-```
-
-``` r
 contr_wi
 #> 
 #> We ran a contrast analysis for the following within contrasts: classic = 0.33; jazz = 0.33; white noise = -0.88; without music = 0.22. This resulted in statistics of t(7) = -3.77; p = 0.9965 and an effect magnitude of g_effectsize = -1.333. Attention: Contrast fits in the opposite direction!