Hello,
I have this code:
proc logistic data=home.finaldata;
class SocIsoSS Age2 MarSta MinNum00_1/ param=ref;
model HHFS2_short= SocIsoSS Age2 MarSta MinNum00_1;
run;
HHFS2_short (secure) is coded as 0=yes 1=no while SocIsoSS (isolation) 0=no, 1=yes.
This is my output:
What I think is the interpretation is that isolated individuals are more likely to be secure compared to those who are to isolated. since the probability being modeled is HHFS2_short=0. However, When I do a chisquare it looks like isolated individuals are more insecure than those who are not isolated which is the opposite of the logistics regression results.
Here are the chisquare results:
I removed the covariates in the logistic model to see if it made any difference, but the results are still the same. Is there something I am interpreting incorrectly?
Hello @astudent,
@astudent wrote:
What I think is the interpretation is that isolated individuals are more likely to be secure compared to those who are to isolated. since the probability being modeled is HHFS2_short=0.
Why do you think that? The estimated odds ratio of 3.450 of "SocIsoSS 0 vs. 1" for being secure (HHFS2_short=0) and its lower confidence limit are clearly greater than one, so -- adjusted for the other covariates -- we would expect a significantly higher percentage of "secure" individuals in the subgroup "SocIsoSS=0" ("non-isolated") than in the subgroup "SocIsoSS=1" ("isolated"). This is consistent with your cross tabulation of SocIsoSS and HHFS2_short: The corresponding empirical odds ratio ignoring the other covariates is 151*125/(58*79)=4.119... (again, clearly greater than 1) and the percentages of "secure" individuals are 65.65 (among the "non-isolated") vs. 31.69 (among the "isolated").
This was very helpful. Thank you so much.
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