Re: Main and interaction effect in Cox Prop Hazards
Posted by
jaycamh on
Sep 23, 2019; 1:22pm
URL: http://spssx-discussion.165.s1.nabble.com/Re-Main-and-interaction-effect-in-Cox-Prop-Hazards-tp5738390p5738401.html
Hi Bruce:
Here is the syntax.
COXREG event
/STATUS=dead(1)
/CONTRAST (sex)=Indicator(1)
/CONTRAST (smoker_cfn)=Indicator
/CONTRAST (HEAVY_DRINKER)=Indicator(1)
/CONTRAST (educ_Lowses)=Indicator(1)
/CONTRAST (HED)=Indicator(1)
/METHOD=ENTER age sex bmi year smoker_cfn educ_lowses HEAVY_DRINKER HED HEAVY_DRINKER*educ_lowses
/PRINT=CI(95)
/CRITERIA=PIN(.05) POUT(.10) ITERATE(20).
Here is how the reference groups are set.
| Categorical
Variable Codingsb,c,d,e,f |
|
|
Frequency |
(1) |
(2) |
| SEXa |
1=Male |
155307 |
0 |
|
|
2=Female |
159312 |
1 |
|
| smoker_cfna |
1.00=Current |
79914 |
1 |
0 |
|
2.00=Former |
74646 |
0 |
1 |
|
3.00=Never |
160059 |
0 |
0 |
| heavy_drinkera |
.00=light/medium |
308903 |
0 |
|
|
1.00=heavy/very heavy |
5716 |
1 |
|
| educ_lowsesa |
0 |
94250 |
0 |
|
|
1 |
220369 |
1 |
|
| HEDa |
3.00=Current |
291130 |
0 |
|
|
4.00=Heavy Episodic |
23489 |
1 |
|
| a. Indicator Parameter Coding |
|
|
|
|
| b. Category variable: SEX
(Sex) |
|
|
|
|
| c. Category variable:
smoker_cfn |
|
|
|
|
| d. Category variable:
heavy_drinker |
|
|
|
|
| e. Category variable:
educ_lowses |
|
|
|
|
| f. Category variable: HED |
|
|
|
|
OUTPUT:
| Variables
in the Equation |
|
B |
SE |
Wald |
df |
Sig. |
Exp(B) |
95.0% CI for Exp(B) |
|
|
|
|
|
|
|
|
Lower |
Upper |
| AGE |
0.085579 |
0.000447 |
36726.27 |
1 |
0 |
1.089348 |
1.088395 |
1.090302 |
| SEX |
-0.42074 |
0.01272 |
1094.055 |
1 |
6.5E-240 |
0.65656 |
0.640393 |
0.673134 |
| BMI |
0.001397 |
0.000552 |
6.410411 |
1 |
0.011345 |
1.001398 |
1.000316 |
1.002482 |
| YEAR |
-0.00649 |
0.001627 |
15.92481 |
1 |
6.59E-05 |
0.993529 |
0.990367 |
0.996702 |
| smoker_cfn |
|
2640.209 |
2 |
0 |
|
|
|
| smoker_cfn(1) |
0.818795 |
0.016262 |
2535.139 |
1 |
0 |
2.267765 |
2.196624 |
2.34121 |
| smoker_cfn(2) |
0.223798 |
0.014984 |
223.0764 |
1 |
1.93E-50 |
1.250819 |
1.214618 |
1.288098 |
| educ_lowses |
0.385774 |
0.015961 |
584.1816 |
1 |
4.6E-129 |
1.470753 |
1.425455 |
1.517489 |
| heavy_drinker |
0.469307 |
0.110958 |
17.88943 |
1 |
2.34E-05 |
1.598886 |
1.286382 |
1.987308 |
| HED |
0.219843 |
0.029364 |
56.05265 |
1 |
7.06E-14 |
1.245881 |
1.176202 |
1.319688 |
| heavy_drinker*educ_lowses |
-0.1332 |
0.115647 |
1.326699 |
1 |
0.249393 |
0.875286 |
0.697768 |
1.097966 |
Fair points, Rich. It would be helpful if the OP posted the syntax.
Also, if I'm using a command that allows factor variables, if it also has
EMMEANS, I like to generate the fitted values (and pairwise contrasts)
corresponding to the interaction term to make sure I've got things right.
Rich Ulrich wrote
> Bruce,
> I hate it when interactions have to be interpreted, especially if it
> is possible that the program generated them and I don't have control.
> Also, telling a program that this is a "factor" and not a continuous
> "variable" raises the problem that, for 0/1, if the program takes "1" as
> the reference group, it reverses the sign of the B obtained. PITA.
>
> Further: if two variables are coded as 0/1 and the interaction is their
> simple product - instead of the "centered" product - then the
> interaction's
> B is correlated with the main-effects' B's, and affects their magnitude in
> the equation that has them all.
>
> I recognize that this OP needs basic help with interpretation of the
> model,
> which you provided. I was skipping that, because the main thing relevant
> to the question is that there /is/ no interaction effect worth worrying
> about, according the Wald test.
>
> --
> Rich Ulrich
-----
--
Bruce Weaver
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