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In proc regress, proc rlogitst and proc survival, you can use a * between two variables (such as two categorical variables or one categorical and one continuous variable) to create an interaction term on the model statement. However, you cannot do this with two continuous variables; you need to create the interaction term in a data step before running the model. For example, srsex and racehpra are categorical variables. In the example below, we create the interaction term between srsex and racehpra.
proc regress data=temp1 filetype=sas design = jackknife; weight rakedw0; jackwgts rakedw1--rakedw80 / adjjack=1; model ab23 = srsex racehpra srsex*racehpra; subgroup srsex racehpra; levels 2 4; run;
S U D A A N
Software for the Statistical Analysis of Correlated Data
Copyright Research Triangle Institute January 2003
Release 8.0.2
Number of observations read : 55428 Weighted count: 23847415
Observations used in the analysis : 1000 Weighted count: 466228
Denominator degrees of freedom : 80
Maximum number of estimable parameters for the model is 8
Weighted mean response is 42.854796
Multiple R-Square for the dependent variable AB23: 0.081618
Variance Estimation Method: Replicate Weight Jackknife
Working Correlations: Independent
Link Function: Identity
Response variable AB23: AB23
----------------------------------------------------------------------
Independent P-value
Variables and Beta T-Test
Effects Coeff. SE Beta T-Test B=0 B=0
----------------------------------------------------------------------
Intercept 47.87 1.81 26.51 0.0000
SRSEX
MALE 1.63 2.41 0.68 0.5011
FEMALE 0.00 0.00 . .
RACEHPRA
LATINO -9.67 2.04 -4.75 0.0000
PACIFIC ISLANDER 4.32 6.03 0.72 0.4757
AIAN -3.47 2.68 -1.29 0.1992
ASIAN 0.00 0.00 . .
SRSEX, RACEHPRA
MALE, LATINO 3.51 3.09 1.14 0.2596
MALE, PACIFIC
ISLANDER -5.64 7.27 -0.78 0.4398
MALE, AIAN -0.39 3.49 -0.11 0.9108
MALE, ASIAN 0.00 0.00 . .
FEMALE, LATINO 0.00 0.00 . .
FEMALE, PACIFIC
ISLANDER 0.00 0.00 . .
FEMALE, AIAN 0.00 0.00 . .
FEMALE, ASIAN 0.00 0.00 . .
----------------------------------------------------------------------
-------------------------------------------------------
Contrast Degrees
of P-value
Freedom Wald F Wald F
-------------------------------------------------------
OVERALL MODEL 8 960.50 0.0000
MODEL MINUS
INTERCEPT 7 8.59 0.0000
INTERCEPT . . .
SRSEX . . .
RACEHPRA . . .
SRSEX * RACEHPRA 3 1.12 0.3457
-------------------------------------------------------
In the next example, we will create an interaction term using a categorical variable, racehpra, and a continuous variable, ae13.
proc regress data=temp1 filetype=sas design = jackknife; weight rakedw0; jackwgts rakedw1--rakedw80 / adjjack=1; model ab23 = ae13 racehpra ae13*racehpra; subgroup racehpra; levels 4; run;
S U D A A N
Software for the Statistical Analysis of Correlated Data
Copyright Research Triangle Institute January 2003
Release 8.0.2
Number of observations read : 55428 Weighted count: 23847415
Observations used in the analysis : 322 Weighted count: 158239
Denominator degrees of freedom : 80
Maximum number of estimable parameters for the model is 8
Weighted mean response is 40.890349
Multiple R-Square for the dependent variable AB23: 0.058683
Variance Estimation Method: Replicate Weight Jackknife
Working Correlations: Independent
Link Function: Identity
Response variable AB23: AB23
----------------------------------------------------------------------
Independent P-value
Variables and Beta T-Test
Effects Coeff. SE Beta T-Test B=0 B=0
----------------------------------------------------------------------
Intercept 46.99 3.16 14.87 0.0000
AE13 -0.15 1.13 -0.14 0.8917
RACEHPRA
LATINO -5.02 3.64 -1.38 0.1715
PACIFIC ISLANDER -9.37 7.35 -1.28 0.2057
AIAN -4.19 4.37 -0.96 0.3396
ASIAN 0.00 0.00 . .
AE13, RACEHPRA
1, LATINO -0.89 1.36 -0.66 0.5113
1, PACIFIC
ISLANDER 4.09 1.65 2.49 0.0150
1, AIAN -0.47 1.45 -0.33 0.7435
1, ASIAN 0.00 0.00 . .
----------------------------------------------------------------------
-------------------------------------------------------
Contrast Degrees
of P-value
Freedom Wald F Wald F
-------------------------------------------------------
OVERALL MODEL 8 257.15 0.0000
MODEL MINUS
INTERCEPT 7 4.35 0.0004
INTERCEPT . . .
AE13 . . .
RACEHPRA 3 0.93 0.4289
AE13 * RACEHPRA 3 4.76 0.0042
-------------------------------------------------------
In the example below, we try to use two continuous variables, ae13 and ae14, to create the interaction term. The error message that was displayed in the log is shown below. If you want to include this type of interaction term in your model, you will need to create it in a data step before running the proc and include it on the model statement.
proc regress data=temp1 filetype=sas design = jackknife; weight rakedw0; jackwgts rakedw1--rakedw80 / adjjack=1; model ab23 = ae13 ae14 ae13*ae14; run;
SEMANTIC ERROR : (Message 452) At most one continuous variable is allowed in each term of the RHS of a MODEL statement
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