dichotomous_2k_2sid {BiVariAn} | R Documentation |
Bivariate Chi squared and Fisher Test analysis for 2 categories.
Description
Generates a HTML table of bivariate Chi squared and Fisher Test analysis for 2 categories. Display a table arranged dataframe with Chi squared statistic, minimum expected frecuencies, Chi squared p value, Fisher Test p value, and Odds ratio with 95 confidence levels. Note that you must recode factors and level the database factors in order to compute exact p values. Variable names can be assigned using table1::label()
function.
Usage
dichotomous_2k_2sid(data, referencevar, flextableformat = TRUE)
Arguments
data |
Data frame from which variables will be extractred |
referencevar |
Reference 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
Returns a dataframe or flextable containing statistical values for Chi squared tests or Fisher's test.
Author(s)
JAFG
Examples
# Not run
# Create a sample dataframe
df <- data.frame(
has = c("Yes", "No", "Yes", "Yes", "No", "No", "Yes"),
smoke = c("Yes", "No", "No", "Yes", "No", "Yes", "No"),
gender = c("Male", "Female", "Male", "Female", "Female", "Male", "Male"))
df$has <- as.factor(df$has)
df$smoke <- as.factor(df$smoke)
df$gender <- as.factor(df$gender)
# Set a value as reference level
df$has <- relevel(df$has, ref= "Yes")
df$smoke <- relevel(df$smoke, ref= "Yes")
df$gender <- relevel(df$gender, ref= "Female")
# Apply function
dichotomous_2k_2sid(df, referencevar="has")
dichotomous_2k_2sid(df, referencevar="has", flextableformat = FALSE)
# Set names to variables
if(requireNamespace("table1")){
table1::label(df$has) <- "Hypertension"
table1::label(df$smoke) <- "Smoking Habits"
table1::label(df$gender) <- "Gender"
dichotomous_2k_2sid(df, referencevar="has", flextableformat = FALSE)
}