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Re: Colombia Gender Scale [message #27742 is a reply to message #26758] |
Wed, 27 September 2023 16:11 |
Deidi
Messages: 14 Registered: March 2021
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Member |
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Good afternoon,
Thanks for your response. That totally makes sense. I have a follow up question for d109. I haven't being able to figure out the following: 1) Whether for a survival model, the value 0 should be coded as 1, or keep it the way it is. 2) How to solve the issue of missing values. If I omit them in the stset set up (e.g, stset years [pw = weight] if years !=.,...), it doesn't give me an error anymore, but then the issue reappears when I'm evaluating the model fit (predict cs, csnell). Is there perhaps an additional restriction (e.g. dropping some other vars) I should run so I don't have such a high number of missing obs? Any other leads, would be much appreciated. Thanks in advance.
timing of first event |
(from d105 series) in |
years after marriage | Freq. Percent Cum.
-------------------------+---------------------------------- -
0 | 6,130 36.78 36.78
.keep if v044==1 & v502>0 // (13,828 observations deleted)
. stset years [pw = weight], failure(ipv_phy_sex==1)
Survival-time data settings
Failure event: ipv_phy_sex==1
Observed time interval: (0, years]
Exit on or before: failure
Weight: [pweight=weight]
------------------------------------------------------------ --------------
24,890 total observations
8,375 event time missing (years>=.) PROBABLE ERROR
------------------------------------------------------------ --------------
16,515 observations remaining, representing
8,567 failures in single-record/single-failure data
47,273 total analysis time at risk and under observation
At risk from t = 0
Earliest observed entry t = 0
Last observed exit t = 30
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