Bivariate analysis for more than 2 groups — continuous

Generates a HTML table of bivariate analysis for 2 groups.

Usage

continuous_multg(data, groupvar, flextableformat = TRUE)

Arguments

data: Data frame from which variables will be extracted.
groupvar: Grouping variable. Must have exactly 2 levels.
flextableformat: Logical operator to indicate the output desired. Default is TRUE. When FALSE, function will return a dataframe format.

Value

A dataframe or flextable containing pvalues for each test along with the normality and homocedasticity tests p values. An extra column will be shown indicating the recommended significant test

Examples

data <- iris

data$Species<-as.factor(data$Species)

continuous_multg(data = data, groupvar = "Species", flextableformat = FALSE)
#>       Variable P_Shapiro_Resid P_Levene P_ANOVA    P_KW Significant_Test
#> 1 Sepal.Length         0.21886  0.00226    <NA> <0.001*   Kruskal-Wallis
#> 2  Sepal.Width         0.32304  0.55552 <0.001* <0.001*            ANOVA
#> 3 Petal.Length         0.03676  <0.001* <0.001* <0.001*   Kruskal-Wallis
#> 4  Petal.Width         0.00387  <0.001* <0.001* <0.001*   Kruskal-Wallis