The TRANSPOSE Procedure

# Example 6: Transposing Data for Statistical Analysis

Procedure features:
 COPY statement VAR statement

This example arranges data to make them suitable for either a multivariate or univariate repeated-measures analysis.

The data are from Chapter 8, "Repeated-Measures Analysis of Variance" in SAS System for Linear Models, Third Edition.

`options nodate pageno=1 linesize=80 pagesize=40;`
 ```data weights; input Program \$ s1-s7; datalines; CONT 85 85 86 85 87 86 87 CONT 80 79 79 78 78 79 78 CONT 78 77 77 77 76 76 77 CONT 84 84 85 84 83 84 85 CONT 80 81 80 80 79 79 80 RI 79 79 79 80 80 78 80 RI 83 83 85 85 86 87 87 RI 81 83 82 82 83 83 82 RI 81 81 81 82 82 83 81 RI 80 81 82 82 82 84 86 WI 84 85 84 83 83 83 84 WI 74 75 75 76 75 76 76 WI 83 84 82 81 83 83 82 WI 86 87 87 87 87 87 86 WI 82 83 84 85 84 85 86 ;```
 ```data split; set weights; array s{7} s1-s7; Subject + 1; do Time=1 to 7; Strength=s{time}; output; end; drop s1-s7; run;```
 ```proc print data=split(obs=15) noobs; title 'SPLIT Data Set'; title2 'First 15 Observations Only'; run;```
`options nodate pageno=1 linesize=80 pagesize=40;`
 `proc transpose data=split out=totsplit prefix=Str;`
 ``` by program subject; copy time strength;```
 ``` var strength; run;```
 ```proc print data=totsplit(obs=15) noobs; title 'TOTSPLIT Data Set'; title2 'First 15 Observations Only'; run;```

 The variables in TOTSPLIT with missing values are used only in a multivariate repeated-measures analysis. The missing values do not preclude this data set from being used in a repeated-measures analysis because the MODEL statement in PROC GLM ignores observations with missing values.