This SAS code snippet demonstrates how to perform a Cartesian product using the proc sql procedure. The resulting table, "dummy02," will have a number of rows equal to the product of the number of rows in "dummy01" and "dummy_treatments" tables.

The SQL query inside the proc sql block selects all columns (indicated by *) from the "dummy01" table and the "dummy_treatments" table. The Cartesian product of these two tables is created, resulting in a new table named "dummy02" that contains all possible combinations of rows from the two tables.

The quit statement is used to end the proc sql block and execute the query.

library(tidyverse)

dummy01<-tribble(
~grouplabel,~statistic,~group,~intord,
"Sex, n(%)","Male",2,1,
"Sex, n(%)","Female",2,2,
"Sex, n(%)","Missing",2,99,
)

dummy_treatments<-tribble(
~treatment,
1,
2,
3,
4,
)

dummy02<-cross_join(dummy01,dummy_treatments)

This R Tidyverse code snippet demonstrates how to create a new data frame named "dummy02" by performing a cross join between two existing data frames, "dummy01" and "dummy_treatments," using the cross_join function from the dplyr package.

The cross_join function takes two data frames as arguments and returns a new data frame that combines every row from the first data frame with every row from the second data frame. The resulting "dummy02" data frame will contain all possible combinations of rows between "dummy01" and "dummy_treatments".