Understanding Society User Support

Dear Theodora,

Can you just clarify - what are you imputing: is it one specific variable (item nonresponse) or is it persons (unit nonresponse)? Have you checked whether you still have missingness that you are imputing if weight is not 0? It is possible possible that the weight corrects already for the nonresponse that you are imputing, so the imputation is not needed.

Also, can you tell me which command you are using for imputation?

Thanks,
Olena

Dear Olena,

Thank you for your reply. I am imputing 5 variables. The 3 of them are linked data about air pollution, greenspace and deprivation and the other 2 are from the individual respondents' dataset about the highest educational qualification and the neighbourhood cohesion.

I haven't checked whether I still have missingness if weight is not 0 but I will check now. Thanks!

My decision for imputing was that in the fully adjusted models were all covariates are included the sample drops a lot.

My command is:

1) I start by defining the complex samples design: mi svyset psu [pweight=c_ythscub_xw], strata(strata) singleunit(scaled)
2) Then I define the variables I want to impute: mi register imputed (variables)
3) I then define the regular variables: mi register regular (variables)
4) Finally: mi impute monotone (regress) (imputed variables)=(regular variables), add(20) nomonotonechk

After the dataset is set I run simple regressions by typing:

mi estimate: svy: regress

However!

- When I run this the imputation syntax I get this message: missing imputed values produced
This may occur when imputation variables are used as independent variables or when independent variables contain missing values. You can specify option force if you wish to proceed anyway.

- Consequently, I forced the imputation and it worked fine but in the fully adjusted models the sample is almost by 1000 cases smaller as if the imputation was not done.

What do you think?

Many thanks,
Dora

Dear Stephanie,

Thank you for your reply. My initial query was to get general advice about the weights and not statistical advice.

Since I was asked what commands I am using in my analysis, I decided to be as explanatory as possible to help your colleague understand the situation.

I presume that the weights are not the problem in my analysis so I will refer to another forum.

Thank you for your help.

Best wishes,
Dora

Dora,

It is hard to judge what goes wrong from your description - the issue could be in many places.

I have just one comment for you: conceptually you don't need svy for imputing linked data. Maybe try to impute it in the original data source? This may or may solve the problem - but this is another point to think about.

Best wishes,
Olena