Understanding Society User Support

Sue,

Thank you for your question.
1. In any multilevel model you should be able to use a weight, sometimes stratification (but if you can't - excluding stratification makes estimates conservative - so not a problem). The cluster variable (PSU) should be one of your levels, usually the highest.
2. If you use k_indinus_lw you don't need to impute anything for missing waves.

Olena

Hi Olena,
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Thanks very much for your advice.

However, I've done a bit of research on the data, and from a geographical multilevel modelling perspective, I'm not sure it would be correct to enter the PSU as the highest level.

This is because the PSU units seem to be very geographically e.g. perhaps postcode districts or sectors.
So say one of my levels is region, then some PSUs are within Regions (judging from the clustering and numbers of PSUs by the Region variable for wave 1 participants). Therefore it wouldn't work spatially-statistically to have PSU as the highest level.

So I wonder if it would be better to use a cross-classified multilevel model to allow for the fact that individuals (within households), may be members of both a PSU and a different overlapping spatial category simultaneously. [And also to avoid using the Regional category].

There is also the issue of the complexity/parsimony of the model to allow for because I already have individuals within time:

1. Largest Area - Cross-classified?
2. PSU ?
3. (Household)
4. Individual
5. Year - LOWEST LEVEL

This is still rather a lot of levels for a Multilevel model!

Which may be very difficult to run and complex to interpret.

Thanks for your input.

Sue CE

Sue,

You have to run a correct model with correct specification, though you don't need to interpret all the levels that you specify. Your analysis is quite unique in the way that you use higher level than PSU, but yes, you PSU needs to be one of the levels, and you of course can have a higher one, like region.
Households would be nested within PSUs. And PSUs in GB are postcode sectors (sometimes old ones as selection was done in 1991, 1999 and 2007) - so some changes could have occured, but I suspect most or all will be nested within regions. You should check this. If a tiny proportion is out, just recode it - I don't think cross-classified model is needed unless there is a large overlap.
Depending on what you study you can avoid household - it is not a longitudinal concept for example...
Also note, that for NI PSU=household.

Hope this helps,
Olena

Hi Olena,

Thanks very much for confirming that PSU is Postcode Sector - I couldn't find this in the User Guides/documentation on Weighting.

Northern Ireland and Scotland are not part of my analysis for various reasons such as differential geographical classification and health service data availability.

Thanks again for your help. Much appreciated.

Sue CE

To find more information on PSUs you should look into sampling documents for UKHLS and BHPS.
Olena