When working with data, we frequently require only a subset of observations/rows for a specific analysis.
So, we need programming features to select the specific subset of rows meeting a filter condition.
There are multiple ways of achieving this result in both SAS and R. Below is one basic approach in SAS and R.
Let us assume that we have the following input data with 19 observations and five variables capturing some basic information about the students of a class.
Name |
Sex |
Age |
Height |
Weight |
Alfred |
M |
14 |
69 |
112.5 |
Alice |
F |
13 |
56.5 |
84 |
Barbara |
F |
13 |
65.3 |
98 |
Carol |
F |
14 |
62.8 |
102.5 |
Henry |
M |
14 |
63.5 |
102.5 |
James |
M |
12 |
57.3 |
83 |
Jane |
F |
12 |
59.8 |
84.5 |
Janet |
F |
15 |
62.5 |
112.5 |
Jeffrey |
M |
13 |
62.5 |
84 |
John |
M |
12 |
59 |
99.5 |
Joyce |
F |
11 |
51.3 |
50.5 |
Judy |
F |
14 |
64.3 |
90 |
Louise |
F |
12 |
56.3 |
77 |
Mary |
F |
15 |
66.5 |
112 |
Philip |
M |
16 |
72 |
150 |
Robert |
M |
12 |
64.8 |
128 |
Ronald |
M |
15 |
67 |
133 |
Thomas |
M |
11 |
57.5 |
85 |
William |
M |
15 |
66.5 |
112 |
Let us assume that we only data for male students for a particular analysis.
Name |
Sex |
Age |
Height |
Weight |
Alfred |
M |
14 |
69 |
112.5 |
Alice |
F |
13 |
56.5 |
84 |
Barbara |
F |
13 |
65.3 |
98 |
Carol |
F |
14 |
62.8 |
102.5 |
Henry |
M |
14 |
63.5 |
102.5 |
James |
M |
12 |
57.3 |
83 |
Jane |
F |
12 |
59.8 |
84.5 |
Janet |
F |
15 |
62.5 |
112.5 |
Jeffrey |
M |
13 |
62.5 |
84 |
John |
M |
12 |
59 |
99.5 |
Joyce |
F |
11 |
51.3 |
50.5 |
Judy |
F |
14 |
64.3 |
90 |
Louise |
F |
12 |
56.3 |
77 |
Mary |
F |
15 |
66.5 |
112 |
Philip |
M |
16 |
72 |
150 |
Robert |
M |
12 |
64.8 |
128 |
Ronald |
M |
15 |
67 |
133 |
Thomas |
M |
11 |
57.5 |
85 |
William |
M |
15 |
66.5 |
112 |
We can create a subset of male students (Sex="M") using the below code.
library(tidyverse)
library(haven)
setwd(dir = "D:/SAS/Home/dev/clinical_sas_samples/mycsg/SAS/SASnR/")
class<-haven::read_sas("class.sas7bdat")
males<-filter(class,Sex=="M")
Example class dataset (sas dataset) can be downloaded from here.