Hi Statalisters,
I want to find out how sensitive the results of my logistic model (or the outputs) are to varying subsamples/ sample sizes) within my data set. Sample data set by "dataex". My outcome is status (binary), co variates are CYP2A_hom(binary), ensmoke( dummy for smoking). I have another variable called Risk with 3 categories, 0=Normal, 1= low risk, 2=high risk. My logistic model is
I want to run this model in a) the full data set, b) among participants whose risk is not equal to 2 and 3) whose risk is not equal to 2 and 3 combined. Basically, I want to know how sensitive my model is towards these 3 sample sizes defined by Risk. Well I could run the model in the three data sets and compare the results. But I have actually multiple models of interaction to run with multiple binary covariates similar to CYP2A_hom. And what I want to know is, is there a formal way in Stata (Some kind of a quantitative/relative measure in Stata program that I can report) to assess the sensitivity of my model outputs towards these 3 risk groups?. If so, how should I perform the analysis/report the measure?
Thanks
I want to find out how sensitive the results of my logistic model (or the outputs) are to varying subsamples/ sample sizes) within my data set. Sample data set by "dataex". My outcome is status (binary), co variates are CYP2A_hom(binary), ensmoke( dummy for smoking). I have another variable called Risk with 3 categories, 0=Normal, 1= low risk, 2=high risk. My logistic model is
Code:
logistic status CYP2A_hom#ensmoke
Code:
* Example generated by -dataex-. To install: ssc install dataex clear input byte status float(CYP2A_hom ensmoke Risk) 0 0 1 0 0 0 1 0 0 0 1 0 1 0 0 2 0 0 1 0 0 1 1 0 1 0 1 2 0 0 0 0 0 0 0 0 1 0 1 2 0 0 0 0 0 0 1 0 1 1 1 0 0 0 1 2 0 1 1 0 1 1 1 0 1 0 1 2 0 0 0 1 0 0 0 0 0 0 1 2 0 0 1 0 1 0 1 0 0 0 1 0 1 0 1 1 0 0 0 0 1 0 1 2 1 0 0 0 0 0 0 0 1 0 1 2 0 0 1 0 0 0 0 0 0 1 1 0 1 0 1 2 0 1 1 0 0 1 1 0 0 0 1 0 0 0 1 0 1 0 1 2 0 0 0 0 0 0 1 0 0 0 0 0 0 1 1 0 0 0 1 0 0 1 1 0 1 0 1 2 0 0 1 0 1 0 1 0 0 1 0 0 0 0 1 0 0 0 0 0 1 0 1 1 0 0 1 2 1 0 1 2 0 0 1 0 0 0 1 0 0 0 0 0 1 0 0 0 0 0 1 0 0 1 1 0 0 0 1 1 0 0 1 0 1 1 1 0 0 1 1 0 0 0 1 0 1 0 0 0 0 0 1 2 1 0 1 2 0 1 1 2 1 0 1 0 0 1 0 0 1 1 0 2 0 0 1 0 1 1 1 2 0 0 1 0 1 0 1 0 0 0 0 0 1 0 1 0 0 0 0 0 1 1 0 0 1 1 1 0 0 0 1 0 0 0 0 0 1 0 1 2 0 0 1 0 1 1 1 0 0 0 0 0 1 1 1 2 0 0 1 0 1 0 1 0 1 0 1 0 0 0 0 0 1 0 1 0 0 0 1 0 1 0 1 0 0 0 1 0 1 0 1 2 0 0 0 0 1 0 1 0 0 1 1 0 0 1 0 0 1 0 1 0 0 0 1 1 1 0 1 0 0 0 0 0 1 0 1 0 0 0 1 1 1 0 1 0 0 1 1 0 1 0 1 1 0 0 1 0 1 1 1 0 0 0 0 0 1 0 1 0 0 0 1 0 1 0 1 1 0 0 1 0 1 0 1 0 0 0 1 1 1 0 1 2 0 0 0 2 1 1 1 2 0 0 1 0 1 0 1 0 0 0 1 0 1 0 1 0 0 0 1 0 1 0 1 0 0 1 1 0 1 0 0 2 0 0 1 0 1 0 1 1 0 1 1 0 1 0 1 0 0 0 1 2 1 0 0 0 0 0 1 2 1 1 1 0 0 1 0 2 1 0 1 1 0 0 1 0 1 0 1 2 0 0 0 0 1 0 1 0 0 0 1 0 1 0 1 0 0 0 1 0 1 0 1 2 0 0 0 0 1 0 1 0 0 0 1 0 1 0 1 0 0 0 0 0 1 0 1 2 0 0 1 0 1 0 1 0 0 0 1 0 1 0 0 2 0 0 1 0 1 0 1 2 0 0 0 0 1 0 1 2 0 1 1 0 1 0 1 2 0 0 1 0 1 1 1 2 0 0 1 2 1 0 1 0 1 0 1 2 0 0 1 0 1 0 1 0 0 0 1 0 1 0 1 0 0 . 1 0 1 0 1 2 0 0 1 1 1 0 1 0 0 0 1 2 1 0 1 0 0 0 1 0 1 0 0 0 0 0 1 0 1 0 1 0 0 0 1 0 1 0 1 2 0 0 1 0 1 0 1 0 0 1 1 0 1 0 0 0 0 0 1 0 1 0 1 0 0 0 0 0 1 1 1 2 0 1 0 0 1 1 1 2 0 0 1 0 1 1 1 0 0 0 1 0 1 1 1 0 0 0 1 0 1 0 1 2 0 0 1 0 1 0 1 2 0 0 1 0 1 0 1 0 0 0 1 0 1 0 1 0 0 0 1 0 1 0 0 0 1 1 1 2 0 0 1 0 1 0 1 2 0 0 1 0 1 0 1 0 0 0 0 0 1 0 1 0 0 0 1 0 0 0 1 0 1 1 1 0 0 0 0 0 1 0 0 2 0 0 1 0 1 1 0 2 0 1 1 0 1 0 1 0 0 0 1 0 1 0 0 2 0 0 1 0 0 0 1 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 1 0 0 0 1 0 0 0 1 0 1 0 1 2 0 1 1 0 1 0 1 2 0 0 1 0 1 0 1 0 0 0 1 0 1 0 1 0 0 0 1 0 1 0 1 1 1 0 1 2 0 0 1 0 1 0 1 2 0 0 1 2 1 0 1 0 0 0 1 0 0 0 1 0 1 0 1 0 0 1 1 0 1 0 1 2 0 1 1 0 1 0 1 0 0 0 1 0 1 0 1 0 0 0 0 0 1 0 0 0 0 1 1 0 1 1 1 0 0 0 1 0 1 0 1 0 0 1 1 0 1 1 1 0 0 0 1 0 1 0 1 2 0 1 0 2 1 0 1 0 0 0 0 0 1 0 1 0 0 1 1 0 1 1 1 2 0 0 1 0 0 0 0 1 1 1 1 2 0 0 0 0 1 0 1 0 0 0 1 0 1 0 1 0 0 0 1 0 1 0 1 1 0 1 0 0 1 1 1 0 0 1 0 0 1 0 1 1 0 0 1 1 1 0 0 0 0 0 0 0 1 1 1 0 0 1 1 0 1 0 1 0 0 0 0 0 1 0 1 0 0 0 1 0 1 0 1 0 0 0 0 0 1 0 1 2 0 1 1 0 1 1 1 0 0 0 1 2 0 0 1 0 1 0 0 2 0 0 1 0 1 0 1 2 0 0 1 0 0 1 1 0 1 0 1 0 0 0 1 0 1 1 1 0 0 0 1 0 1 0 1 2 0 0 1 1 1 0 1 0 0 0 1 2 1 0 1 2 0 0 1 0 1 0 1 2 0 0 1 0 1 0 1 0 0 0 0 0 1 0 0 0 0 0 0 0 1 0 1 0 0 0 1 2 1 0 0 0 0 0 0 2 1 1 1 0 0 0 1 0 1 0 1 0 0 0 1 0 1 0 1 2 0 0 1 1 1 0 1 2 0 0 1 0 1 0 1 0 0 1 1 0 1 1 1 2 0 1 1 1 1 0 0 0 0 0 0 0 1 0 1 0 0 0 1 0 1 0 0 0 0 1 1 2 1 1 1 0 0 0 1 0 1 0 1 0 0 0 1 2 1 0 1 0 0 0 1 2 1 1 1 2 0 0 1 0 1 0 1 1 0 0 0 2 1 0 1 2 0 0 1 0 1 0 1 2 0 0 1 0 1 0 1 0 0 0 1 0 1 1 0 0 0 0 1 0 1 0 1 0 0 0 0 2 1 0 1 2 0 0 1 0 1 0 0 2 0 0 0 0 1 0 1 2 0 0 1 2 1 0 1 2 0 0 1 0 1 0 1 0 0 0 1 0 1 1 1 0 0 0 1 0 1 0 1 0 0 1 1 0 0 0 1 0 1 0 1 0 0 1 0 0 0 1 1 0 1 0 1 2 0 0 1 0 1 0 0 2 0 1 1 0 1 0 1 2 1 0 1 0 0 0 0 0 1 0 1 2 1 0 0 2 0 0 1 0 1 0 0 0 0 0 0 0 1 1 1 0 0 1 1 0 1 0 1 0 0 0 1 2 1 0 1 0 0 0 1 2 1 0 1 0 0 0 0 0 1 0 1 0 0 0 1 0 1 0 1 2 1 0 1 0 0 0 1 0 1 0 1 2 0 0 0 0 1 1 1 0 1 0 1 1 0 1 0 0 1 0 1 0 0 0 0 0 1 1 1 0 0 0 1 0 1 0 1 2 0 0 1 0 1 0 0 2 0 0 0 0 1 1 1 0 0 0 0 0 1 1 1 0 0 0 0 0 1 . 0 2 0 0 0 0 1 0 1 0 0 1 0 0 1 0 0 2 1 0 1 0 0 0 1 1 1 0 0 2 0 0 1 0 1 0 1 2 0 0 1 2 1 0 1 0 0 0 1 0 1 0 1 2 0 0 1 2 1 1 1 0 0 0 0 0 1 0 0 0 0 0 1 0 1 0 1 0 0 1 0 0 1 1 1 0 0 1 1 0 1 0 1 0 0 0 0 0 1 0 1 0 0 1 0 0 1 0 0 0 0 0 1 0 1 1 1 0 0 0 1 0 1 0 1 0 0 0 1 0 1 0 0 2 0 1 0 0 1 1 0 2 0 0 1 0 0 0 0 0 1 0 1 0 0 0 0 0 1 1 1 2 0 0 1 0 1 0 1 2 0 0 0 0 1 0 1 0 0 0 1 0 1 0 1 2 0 0 1 0 1 0 1 2 0 0 0 0 1 0 1 0 0 0 1 0 1 0 1 0 0 0 1 0 1 0 1 0 0 0 1 0 1 0 1 2 0 0 1 0 1 0 1 1 0 0 0 0 0 0 1 0 1 0 1 0 0 0 0 0 1 0 1 0 0 0 0 0 1 0 1 0 0 1 1 0 1 0 1 0 0 0 1 0 1 0 1 1 0 0 1 0 1 0 1 0 0 0 1 0 1 0 1 0 0 0 1 0 1 0 0 0 0 0 1 0 1 1 1 0 0 0 1 0 1 1 1 0 0 0 1 0 1 0 1 2 0 0 0 0 0 0 1 0 1 0 0 0 0 1 1 0 1 0 1 1 0 0 0 0 1 0 1 0 0 0 1 0 1 0 1 0 0 0 1 0 1 1 1 0 0 0 0 0 1 0 1 2 0 0 0 0 1 0 1 2 0 0 1 0 0 0 1 1 1 0 1 2 0 0 1 0 1 0 0 0 0 0 1 1 0 0 1 0 1 0 0 0 0 0 1 0 1 0 1 2 0 0 1 0 1 0 1 2 0 0 1 0 1 0 1 0 0 0 1 0 1 0 1 0 0 0 1 0 1 0 0 0 0 0 0 0 1 0 1 0 0 0 0 0 1 0 1 0 0 0 1 1 1 0 1 0 0 0 0 0 1 0 1 0 0 0 1 0 0 0 1 2 1 0 0 2 0 0 0 2 1 0 1 2 0 0 1 0 1 0 1 2 0 1 0 0 1 0 0 0 0 1 1 0 1 0 1 1 1 0 1 0 0 1 1 0 1 0 1 2 0 0 1 0 1 0 1 2 0 0 0 0 1 0 0 2 0 0 1 0 1 0 1 2 0 0 1 0 1 0 1 0 0 0 1 0 1 0 1 0 1 0 1 2 0 0 0 2 0 0 1 0 1 0 0 2 0 0 1 0 0 0 1 2 1 0 0 0 0 0 0 0 1 0 1 0 0 0 0 0 1 0 1 0 0 0 1 0 1 0 1 2 0 0 0 0 1 0 1 0 0 0 0 0 1 0 1 2 0 0 0 0 1 0 1 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 1 0 1 2 0 0 1 0 1 0 1 2 1 0 1 0 0 0 1 0 1 1 1 2 0 0 1 0 1 0 1 2 0 0 1 0 0 0 1 0 1 0 1 0 0 0 1 0 0 0 1 0 1 0 1 2 0 0 1 0 1 1 1 0 0 0 0 0 1 0 0 0 0 0 1 0 1 0 1 2 0 0 1 2 1 0 1 0 0 0 1 0 1 1 0 2 0 0 0 0 1 0 0 2 0 0 0 0 1 0 1 0 0 0 0 0 1 0 1 0 1 0 1 0 1 0 1 0 0 0 1 0 1 0 0 0 0 0 0 0 1 0 1 0 0 0 1 0 1 0 1 2 0 0 0 0 1 0 1 0 0 0 1 0 1 0 1 0 0 0 1 0 1 0 0 0 1 1 0 0 0 0 1 0 1 0 1 0 0 0 1 0 1 0 0 2 1 1 1 2 0 0 1 2 1 0 0 2 0 1 0 2 1 0 1 2 0 0 1 0 1 0 0 2 0 0 1 0 1 0 1 0 0 0 1 0 0 0 1 0 1 0 1 0 0 0 0 0 1 0 0 2 0 0 1 0 0 0 1 0 1 0 0 0 0 1 0 0 1 0 1 2 0 0 1 2 1 0 0 0 0 1 1 0 0 0 1 2 1 1 1 0 0 0 1 0 1 0 1 0 0 0 1 0 1 0 1 0 1 0 1 1 0 0 0 0 1 0 1 2 0 0 1 0 1 0 1 0 0 0 1 0 0 0 1 0 1 0 1 0 0 1 1 0 1 1 1 1 0 1 1 0 1 0 1 1 0 0 1 0 1 0 1 0 0 0 1 0 1 0 0 2 0 0 1 0 1 0 1 2 0 0 1 0 1 0 1 0 0 0 1 2 1 0 1 0 0 0 1 0 1 0 1 2 0 0 0 0 0 0 1 0 0 0 1 0 1 0 1 0 0 0 1 0 1 0 1 0 0 0 1 0 0 0 1 0 1 0 1 2 0 0 1 0 1 0 1 0 0 0 1 0 1 0 0 2 0 1 1 0 1 0 1 0 0 0 1 0 1 1 1 0 0 1 1 0 1 0 1 0 0 0 1 0 1 0 1 0 0 0 1 0 1 0 1 0 0 1 1 0 1 0 0 0 0 1 1 0 1 1 0 2 0 0 1 0 0 0 1 2 1 0 1 0 0 0 0 0 0 0 1 0 1 0 1 0 0 0 1 0 0 0 1 0 1 1 1 0 0 1 1 0 1 . 1 0 1 1 1 2 0 0 1 0 1 0 0 0 1 0 1 2 0 0 1 2 0 1 1 0 1 0 1 1 0 0 1 0 0 0 1 0 1 0 1 0 0 0 0 0 1 0 1 2 0 0 1 0 1 0 1 0 1 0 1 2 0 0 1 0 1 0 1 2 0 1 1 2 1 0 1 0 0 0 1 0 1 0 1 2 0 0 1 0 1 0 0 0 1 0 0 0 0 0 1 0 1 0 1 2 0 0 0 0 1 0 1 0 0 0 1 0 1 0 1 0 0 0 1 2 0 0 0 0 1 0 1 0 0 0 1 0 1 0 1 2 0 0 1 0 1 0 0 0 0 0 1 0 1 0 1 2 0 0 1 2 1 1 1 0 0 0 0 0 1 0 1 0 0 0 1 0 1 1 0 2 0 0 1 0 1 1 1 0 0 0 1 0 1 0 0 2 0 0 1 2 1 0 1 0 0 0 0 2 1 0 1 2 0 1 1 0 1 0 1 0 0 0 0 0 1 0 1 2 0 0 1 0 1 0 1 2 0 0 1 0 1 1 1 2 0 0 1 2 1 1 1 2 0 0 0 0 1 1 1 2 0 0 0 0 1 0 1 0 0 1 1 0 1 0 1 0 0 0 0 0 1 0 1 0 0 0 1 0 1 1 1 2 0 0 1 0 0 1 1 0 1 0 1 0 0 0 0 0 1 0 0 0 0 1 1 0 1 0 0 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 2 1 0 1 0 end label values status Stat label def Stat 0 "Control", modify label def Stat 1 "Case", modify label values CYP2A_hom cyp_hom label def cyp_hom 0 "TT/CC", modify label def cyp_hom 1 "CT", modify label values Risk Risk label def Risk 0 "Normal", modify label def Risk 1 "low risk", modify label def Risk 2 "high risk", modify
