Linking all waves of BHPS and UKHLS: Inconsistencies?
I've merged all the waves of the BHPS and Understanding Society into one master data file in the long-format (I have one row per person per wave). To check whether this has worked out correctly, I checked whether any respondents had changes in time-invariant variables like their sex. Doing that, I found quite a number of mismatches: Using the variable "sex" by "pidp", there was a change of sex in 15417 rows (and no change in 558476 rows). If I use "sex_dv", there is a change of sex in only 17 rows (no change in 279717 rows; sex_dv has a large number of missing values).
Is it possible that there are that many inconsistencies or is it more likely that I did anything wrong in the process of merging the datasets?
Updated by Alita Nandi over 2 years ago
- Status changed from New to Feedback
- Assignee changed from Alita Nandi to Nicole Schwitter
- % Done changed from 0 to 80
- Private changed from Yes to No
Without looking at your code I cannot comment but I can say that when I appended 25 waves I too find similar inconsistencies. The reason you are getting these inconsistencies is because of proxy interviews. For these cases sex is coded as -7. We will look into why sex=-7 for proxy interviews as the missing value code of -7 is reserved for cases where the information is missing for proxy interviews - and that is not the case for sex.
After creating the long format file of 25 waves, I produced the mean of sex, sex_mean1 and counted mismatches of this mean with individual wave specific value of sex. I too found 15458 inconsistencies
bys pidp: egen sex_mean1=mean(sex)
cou if sex~=sex_mean1
Then I recoded proxies to missing and repeated the exercise and found 2545 mismatches.
recode sex -7=.
bys pidp: egen sex_mean2=mean(sex)
cou if sex~=sex_mean2
And when I restricted this to only those cases where sex is not missing the number of mismatches goes down to 492.
cou if sex~=sex_mean2 & sex<.
Understanding Society User Support Team