Re: Main and interaction effect in Cox Prop Hazards

Posted by Rich Ulrich on Sep 20, 2019; 9:06pm
URL: http://spssx-discussion.165.s1.nabble.com/Re-Main-and-interaction-effect-in-Cox-Prop-Hazards-tp5738390p5738393.html

(I'm reading the distribution from SPSSX-L directly, ,using Outlook, and the table is formatted fine for me.)

No - you do not have an effect worth mentioning for the interaction that you have coded.

In fact, it is somewhat impressive that the Wald chi-squared for it is less than 1; it is not

even picking up trivial, artifactual contributions from anywhere.

Do you know how to read those "Wald" numbers that end in E?  For Age, Wald is 3.719E4.

"3.719E4"  is a notation where "E4" stands for "10 to the 4th":  move the decimal over

by 4 places, so the actual number is approximately 37,190.  Apparently your sample size

is "hundreds of thousands" for it to generate a chi-squared type of test that is that large.

Just like with any ANOVA table, your emphasis should be on the larger tests values when

their sizes vary by orders of magnitude.  Why?  For example:  If your "age" is at all confounded with

BMI (which it probably is), then it is easy to imagine that the /observed/ BMI effect, Wald= 6.844,

will disappear if there were a more complete control for Age. It would not be unreasonable,

IMHO, to "look at" a re-run of the test where Age is entered as dozens of separate years, as dummy

categories, so that there are K-1  d.f.  for age variables (including "linear") where K is the number of

separate ages.   - Looking at the effects on other coefficients will give you /illustrations/ of how

the largest effects can create artifacts.

I'm not sure what Bruce was saying about coefficients. 

--

Rich Ulrich

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From: SPSSX(r) Discussion <[hidden email]> on behalf of i Jay <[hidden email]>
Sent: Friday, September 20, 2019 12:53 PM
To: [hidden email] <[hidden email]>
Subject: Re: Main and interaction effect in Cox Prop Hazards

 

Hello,

I need help.

I am doing a Cox proportional hazards model in SPSS. I have Low SES and Heavy drinking as 2 main effects and LOW SES x Heavy drinking as interaction effect in the model.

We have stronger (and significant) effects for each main effect but the interaction term is coming protective which is against the theory. Not sure if I am doing it wrong ... see the SPSS result below.

I have, Low SES 0 is reference; 1=low SES

Heavy drinking 0 is reference; 1=heavy drinking.


in fact when I make interaction of alcohol and smoking it’s also coming protective...
Is my Interpretation wrong or is there any other way my syntax should have been formed.

Variables in the Equation
	B	SE	Wald	df	Sig.	Exp(B)	95.0% CI for Exp(B)
							Lower	Upper
AGE	.085	.000	3.719E4	1	.000	1.089	1.088	1.090
SEX - FEMALE	-.433	.013	1.179E3	1	.000	.649	.633	.665
BMI	.001	.001	6.844	1	.009	1.001	1.000	1.003
YEAR	-.006	.002	15.634	1	.000	.994	.990	.997
smoker_cfn			2.716E3	2	.000
smoker_cfn(1)	.827	.016	2.600E3	1	.000	2.285	2.214	2.359
smoker_cfn(2)	.223	.015	221.735	1	.000	1.250	1.214	1.287
heavy_drinker	.566	.110	26.427	1	.000	1.761	1.419	2.186
educ_lowses	.393	.016	608.737	1	.000	1.481	1.436	1.528
heavy_drinker*educ_lowses	-.094	.116	.656	1	.418	.911	.726	1.

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