SAS Code for Sample Size and Power Calculation in Two-Sample Comparisons

SAS code snippets are provided for conducting power and sample size analyses in two-sample comparisons using the TWOSAMPLEMEANS statement. The code covers scenarios such as two-sample t-tests assuming equal variances, unbalanced designs, unequal variances, and more. Examples and syntax are included to demonstrate how to specify sample sizes and calculate power for different experimental setups.

• SAS
• Sample Size
• Power Calculation
• Two-Sample Comparison
• Statistical Analysis

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1. SAS code for sample size/power calculation in two-sample comparisons

2. Procedure : power The TWOSAMPLEMEANS statement performs power and sample size analyses for pooled and unpooled tests, equivalence tests, and confidence interval precision involving two independent samples.

3. 1. Two-Sample t Test Assuming Equal Variances You can use the NPERGROUP= option in a balanced design and express effects in terms of the mean difference, as in the following statements. Default values for the DIST=, SIDES=, NULLDIFF=, and ALPHA= options specify a two-sided test for no difference with a normal distribution and a significance level of 0.05. proc power; twosamplemeans test=diff meandiff = 7 stddev = 12 npergroup = 50 power = .; run;

4. proc power; twosamplemeans test=diff meandiff = 7 stddev = 12 npergroup = . power = 0.8; run;

5. You can also specify an unbalanced design by using the NTOTAL= and GROUPWEIGHTS= options and express effects in terms of individual group means: proc power; twosamplemeans test=diff groupmeans = 8 | 15 stddev = 4 groupweights = (2 3) ntotal = . power = 0.9; run;

6. Another way to specify the sample sizes is with the GROUPNS= option: proc power; twosamplemeans test=diff groupmeans = 8 | 15 stddev = 4 groupns = (25 40) power = .; run;

7. 2. Two-Sample Satterthwaite t Test Assuming Unequal Variances The following statements demonstrate a power computation for the two-sample Satterthwaite t test allowing unequal variances. Default values for the DIST=, SIDES=,NULLDIFF=, and ALPHA= options specify a two-sided test for no difference with a normal distribution and a significance level of 0.05. proc power; twosamplemeans test=diff_satt meandiff = 3 groupstddevs = 5 | 8 groupweights = (1 2) ntotal = 60 power = .; run;

8. Exercise data one; input y type @@; datalines; 65 1 81 1 57 1 66 1 82 1 82 1 67 1 59 1 75 1 70 1 run; procttest data=one; class type; var y; run; 64 2 71 2 83 2 59 2 65 2 56 2 69 2 74 2 82 2 79 2

10. procpower; twosamplemeans test=diff meandiff = 2 stddev = 9.3155 npergroup = 10 power = .; run; procpower; twosamplemeans test=diff meandiff = 1 stddev = 9.3155 npergroup = . power = 0.9; run;