Synergy in SaskatoonIt feels like a while since I last wrote on these pages… probably because I’ve spent quite a bit of time setting up the user group meetings on the SAS Canada Community. I’m enjoying the challenge – and freedom, to be honest …
Example 9.9: Simplifying R using the mosaic package (part 1)
While both SAS and R are powerful systems for statistical analysis, they can be frustrating to new users or those learning statistics for the first time. RThe mosaic package is designed to help simplify the interface for such new users, while allowing …
Example 9.9: Simplifying R using the mosaic package (part 1)
While both SAS and R are powerful systems for statistical analysis, they can be frustrating to new users or those learning statistics for the first time. RThe mosaic package is designed to help simplify the interface for such new users, while allowing …
Example 9.9: Simplifying R using the mosaic package (part 1)
While both SAS and R are powerful systems for statistical analysis, they can be frustrating to new users or those learning statistics for the first time. RThe mosaic package is designed to help simplify the interface for such new users, while allowing …
Counting the number of missing and non-missing values for each variable in a data set.
/* create sample data */
data one;
input a $ b $ c $ d e;
cards;
a . a 1 3
. b . 2 4
a a a . 5
. . b 3 5
a a a . 6
a a a . 7
a a a 2 8
;
run;
/* create a format to group missing and non-missing */
proc format;
value $missfmt ‘ ‘=’m…
Counting the number of missing and non-missing values for each variable in a data set.
/* create sample data */
data one;
input a $ b $ c $ d e;
cards;
a . a 1 3
. b . 2 4
a a a . 5
. . b 3 5
a a a . 6
a a a . 7
a a a 2 8
;
run;
/* create a format to group missing and non-missing */
proc format;
value $missfmt ‘ ‘=’m…