The hardware and bandwidth for this mirror is donated by dogado GmbH, the Webhosting and Full Service-Cloud Provider. Check out our Wordpress Tutorial.
If you wish to report a bug, or if you are interested in having us mirror your free-software or open-source project, please feel free to contact us at mirror[@]dogado.de.
The goal of pomcheckr is to implement the method described by UCLA Statistical Consulting for checking if the proportional odds assumption holds for a cumulative logit model.
You can install the released version of pomcheckr from CRAN with:
install.packages("pomcheckr")You can install the development version from GitHub with:
# install.packages("devtools")
devtools::install_github("melissa-wong/pomcheckr")The following example uses the default syntax:
library(pomcheckr)
plot(pomcheck("Species", c("Sepal.Length", "Sepal.Width"),
iris))
This is the equivalent example using formula syntax:
plot(pomcheck(Species ~ Sepal.Length + Sepal.Width, iris))
This example shows how to access and view the pomcheck
object underlying the plots:
p <- pomcheck(Species ~ Sepal.Length + Sepal.Width, iris)
summary(p)
#> Length Class Mode
#> [1,] 4 grouped_df list
#> [2,] 4 grouped_df listprint(p)
#> [[1]]
#> # A tibble: 4 x 4
#> # Groups: Sepal.Length [4]
#> Sepal.Length `Species_>=1` `Species_>=2` `Species_>=3`
#> <fct> <dbl> <dbl> <dbl>
#> 1 [4.3,5.1] Inf -1.97 -3.69
#> 2 (5.1,5.8] Inf 0.580 -1.92
#> 3 (5.8,6.4] NA Inf 0.0572
#> 4 (6.4,7.9] NA Inf 1.06
#>
#> [[2]]
#> # A tibble: 4 x 4
#> # Groups: Sepal.Width [4]
#> Sepal.Width `Species_>=1` `Species_>=2` `Species_>=3`
#> <fct> <dbl> <dbl> <dbl>
#> 1 [2,2.8] Inf 3.83 -0.388
#> 2 (2.8,3] Inf 1.42 -0.452
#> 3 (3,3.3] Inf 0.547 -0.405
#> 4 (3.3,4.4] Inf -1.64 -1.86
#>
#> attr(,"class")
#> [1] "pomcheck" "list"These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.