I am using multivariable Cox regression. My main exposure (TS_WHO_gold) is a categorical variable with three levels (normal, osteopenia, osteoporosis). Several of the covariates in the model have missing data, which are deleted by listwise deletion. My question is: How can I find the count of each exposure category after running the Cox regression? I tried merely -tab- as shown below (2,686), but it doesn't match the number of observations (2,346) in the output from -stcox- (see below).
Code:
. tab TS_WHO_gold if BMIcat_gold!=. & SmoStatPackYrs_gold_missing!=. & SES_gold!=. & COP > Dcat_gold!=. & physact_gold!=. & alcohol_gold!=. & PartAg_gold!=. & CVD_gold!=. & canc > er_gold!=. & chrondisADL_gold!=. & diabetes_gold!=. & musc_skel_gold!=. WHO BMD | categories | for the HUNT | COPD cohort | using | forearm and | total hip | DXA meas | Freq. Percent Cum. -------------+----------------------------------- normal | 1,737 64.67 64.67 osteopenia | 565 21.03 85.70 osteoporosis | 384 14.30 100.00 -------------+----------------------------------- Total | 2,686 100.00
Code:
. stcox i.TS_WHO_gold i.Sex ib2.BMIcat_gold i.SmoStatPackYrs_gold_missing i.SES_gold i.C > OPDcat_gold i.physact_gold i.alcohol_gold c.PartAg_gold i.CVD_gold i.cancer_gold i.chr > ondisADL_gold i.diabetes_gold i.musc_skel_gold if (goldcopd_HUNT==1 | goldcopd_HUNT==2 > ) & (TS_HUNT!=.) & (PartAg_gold>=40.0 & PartAg_gold<=85.0) failure _d: RegisStat == 5 analysis time _t: (enddate-origin)/365.25 origin: time PartDat_gold id: PID_107945 Iteration 0: log likelihood = -8426.7323 Iteration 1: log likelihood = -7838.0546 Iteration 2: log likelihood = -7797.353 Iteration 3: log likelihood = -7797.1758 Iteration 4: log likelihood = -7797.1757 Refining estimates: Iteration 0: log likelihood = -7797.1757 Cox regression -- Breslow method for ties No. of subjects = 2,346 Number of obs = 2,346 No. of failures = 1,187 Time at risk = 27880.69268 LR chi2(29) = 1259.11 Log likelihood = -7797.1757 Prob > chi2 = 0.0000
Best regards,
Sigrid
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