st: Test for effect modification/interaction using svy

["Schmutz Einat" <schmutze@student.ethz.ch>]

Dear all



I am trying to statistically compare two cox regression models (nested) using svy commands to see whether effect modification exists. What I did is I included an interaction term (2 categorical variables) and run the adjusted Wald test (as postestimation commands normally used after stcox, such as lrtest, don't work with svy).



Syntax for the two models I want to compare („i.vdpcat“ is the exposure variable, “var1-4” are confounding variables and “excessVA” is the potential effect modifier):



svyset [w=weightvar], psu(psuvar) strata(straatavar) vce(linearized)
stset timevar, failure (failvar)

svy, subpop(if ...): stcox var1 var2 i.var3 i.var4 i.vdpcat

svy, subpop(if ...): stcox var1 var2 i.var3 i.var4 i.vdpcat#excessVA

testparm i.vdpcat#excessVA


What I get is:
----------------------------------------------------------------------------------
                 |             Linearized
              _t | Haz. Ratio   Std. Err.      t    P>|t|     [95% Conf. Interval]
-----------------+----------------------------------------------------------------
...
...
vdpcat#exbloodVA |
            1 2  |   1.170165   .1309874     1.40   0.167     .9344425    1.465352
            2 1  |   .9572346   .0975444    -0.43   0.670     .7799799    1.174771
            2 2  |   .9208137   .1008386    -0.75   0.455     .7389192    1.147484
            3 1  |   .8220665   .0850683    -1.89   0.064     .6677197    1.012092
            3 2  |   .9301641   .0882042    -0.76   0.449     .7687764    1.125432
            4 1  |   .8522502   .0738444    -1.85   0.071     .7160554    1.014349
            4 2  |   .8321073   .0976341    -1.57   0.124     .6573199    1.053372
----------------------------------------------------------------------------------

. testparm i.vdpcat#exbloodVA

Adjusted Wald test

 ( 1)  1b.vdpcat#2.exbloodVA = 0
 ( 2)  2.vdpcat#1b.exbloodVA = 0
 ( 3)  2.vdpcat#2.exbloodVA = 0
 ( 4)  3.vdpcat#1b.exbloodVA = 0
 ( 5)  3.vdpcat#2.exbloodVA = 0
 ( 6)  4.vdpcat#1b.exbloodVA = 0
 ( 7)  4.vdpcat#2.exbloodVA = 0

       F(  7,    43) =    3.12
            Prob > F =    0.0094

What I understand is that there is a statistically significant difference in survival among the 8 groups. Now, can I conclude that, since the Wald test is significant (p≤0.05), there is an interaction between vdpcat and exbloodVA and that the second model (including the interaction variable) is the better/more accurate model in predicting my outcome (survival)?

In addition, what does the following test (using ##) tell me? Is this the accurate way to test a possible interaction between vdpcat and excessVA?

svy, subpop(if ...): stcox var1 var2 i.var3 i.var4 i.vdpcat##excessVA

testparm i.vdpcat#excessVA


----------------------------------------------------------------------------------
                 |             Linearized
              _t | Haz. Ratio   Std. Err.      t    P>|t|     [95% Conf. Interval]
-----------------+----------------------------------------------------------------
...
...
     2.exbloodVA |   1.170165   .1309874     1.40   0.167     .9344425    1.465352
                 |
          vdpcat |
              2  |   .9572346   .0975444    -0.43   0.670     .7799799    1.174771
              3  |   .8220665   .0850683    -1.89   0.064     .6677197    1.012092
              4  |   .8522502   .0738444    -1.85   0.071     .7160554    1.014349
                 |
exbloodVA#vdpcat |
            2 2  |    .822065   .1190204    -1.35   0.182     .6145367    1.099675
            2 3  |   .9669529    .157167    -0.21   0.837     .6975098     1.34048
            2 4  |   .8343821   .1049943    -1.44   0.157     .6479522    1.074452
----------------------------------------------------------------------------------

. testparm i.vdpcat#exbloodVA

Adjusted Wald test

 ( 1)  2.exbloodVA#2.vdpcat = 0
 ( 2)  2.exbloodVA#3.vdpcat = 0
 ( 3)  2.exbloodVA#4.vdpcat = 0

       F(  3,    47) =    1.11
            Prob > F =    0.3540


Thanks for your help.



Einat

*
*   For searches and help try:
*   http://www.stata.com/help.cgi?search
*   http://www.stata.com/support/faqs/resources/statalist-faq/
*   http://www.ats.ucla.edu/stat/stata/