All of the effects that you can test using the effects statement can also be tested using the contrast statement, but the purpose of the effects statement is to make testing effects easier. The effects statement is available in all modeling procedures in SUDAAN, and it may be repeated multiple times within a single call to a procedure. Three types of hypothesis tests are easily accomplished with the effects statement: testing multiple main effects and/or interactions simultaneously; testing general linear contrasts; and testing main effects in the presence of interactions, such obtaining the simple main effect of a variable. Below is an example showing how to use the effects statement in proc regress. (Please see pages 465-467 of the SUDAAN manual for more information regarding the effects statement in proc regress.) Note that the variables listed on the effects statement must be in the same order as those listed on the model statement. The name option (given after the slash on the effects statement) is optional, but we encourage people to use so that it is easier to find these results in the output (in this example, the very last line of the output).
proc regress data=temp1 filetype=sas design = jackknife; weight rakedw0; jackwgts rakedw1--rakedw80 / adjjack=1; model ae13 = ae14 srsex racehpra; subgroup srsex racehpra; levels 2 4; effects racehpra = (1 0 0 -1) / name = "This is my contrast"; run;Number of observations read : 55428 Weighted count: 23847415 Observations used in the analysis : 6727 Weighted count: 3976584 Denominator degrees of freedom : 80 Maximum number of estimable parameters for the model is 6 Weighted mean response is 2.665200 Multiple R-Square for the dependent variable AE13: 0.262197 Variance Estimation Method: Replicate Weight Jackknife Working Correlations: Independent Link Function: Identity Response variable AE13: Number of drinks on the days drinking alcohol ---------------------------------------------------------------------- Independent P-value Variables and Beta T-Test Effects Coeff. SE Beta T-Test B=0 B=0 ---------------------------------------------------------------------- Intercept 1.00 0.06 16.58 0.0000 Self-reported gender MALE 0.87 0.07 12.45 0.0000 FEMALE 0.00 0.00 . . Race - UCLA CHPR Definition LATINO 1.03 0.07 14.95 0.0000 PACIFIC ISLANDER 0.67 0.38 1.78 0.0793 AIAN 0.73 0.19 3.91 0.0002 ASIAN 0.00 0.00 . . Number of times having 5 or more drinks in past month 0.39 0.04 10.41 0.0000 ---------------------------------------------------------------------- ------------------------------------------------------- Contrast Degrees of P-value Freedom Wald F Wald F ------------------------------------------------------- OVERALL MODEL 6 921.40 0.0000 MODEL MINUS INTERCEPT 5 90.79 0.0000 INTERCEPT . . . SRSEX 1 155.04 0.0000 RACEHPRA 3 82.09 0.0000 AE14 1 108.44 0.0000 This is my contrast 1 223.63 0.0000 -------------------------------------------------------