Support #2281
openWeights for longitudinal analysis - high zero-weighted numbers; and selecting weights
10%
Description
Hi,
I'm carrying out some longitudinal analysis and have two questions about the longitudinal weights. For context: I'm analysing employment transitions using consecutive wave pairs (e.g., job characteristics at Wave 4 predicting economic (in)activity at Wave 5; job charcteristics at Wave 6 predicting economic (in)activity at Wave 7, e.t.c). At this initial stage of analysis I'm actually going to try to analyse each pair independently rather than as a continuous panel, partly to boost sample size.
Firstly, for each pair (4-5, 6-7, 8-9, 10-11, 12-13), I'm wondering if I should in fact use the longitudinal weight for that specific wave combination (e.g., indscub_lw* for waves involving 2-5, and indscui_lw for later pairs)? The weighting documentation might be read as implying that I should use only one consistent weight, but as I'm grouping with pairs I actually think this wouldn't make sense. Instead, I propose to use different weights depending on the pairs, simply renaming the appropriate weight depending on the wave pair into a consistent combined name so I can insert them into the survey design.
Secondly, I notice there are quite a lot of zero-weighted individuals in my wave pairs. When filtering to those in paid work at the even-numbered waves, and who respond to both that wave and the wave after, about 40% of values seem to be zero weighted in each pair. This contrasts with a considerably smaller number of zero-weighted values for the cross-sectional version of the weight (i.e. indscub/ui_xw). Is this correct? I wanted to clarify this before proceeding as that seems like quite a lot of values to lose, so perhaps it's more apporpriate for me to create my own bespoke weight so as to not lose the values - though unsure if the process for that would be too complex and time-consuming.
Best wishes,
Tom
- Note I'm also using self-completion health questionnaire data for some analysis, so am using the self-completion weight. I don't this is the cause for the large number of zero-weighted values.
Updated by Understanding Society User Support Team about 9 hours ago
- Category set to Weights
- Status changed from New to In Progress
- Assignee changed from Understanding Society User Support Team to Olena Kaminska
- % Done changed from 0 to 10
- Private changed from Yes to No
Many thanks for your enquiry. The Understanding Society team is looking into it and we will get back to you as soon as we can. We aim to respond to simple queries within 48 hours and more complex issues within 7 working days.
Updated by Olena Kaminska about 7 hours ago
Thomas,
Thank you. Yes, you still need longitudinal weights with your set up of pooled analysis. I suggest you read question 15 here (https://www.understandingsociety.ac.uk/wp-content/uploads/working-papers/2024-01.pdf). Note, you have longitudinal pooled analysis.
Our longitudinal weights are created for a situations when all waves up to wave n are used in an analysis. In your situation you are using only last two waves. So if you want you can create your own tailored weight. Here is our online course on this: https://www.understandingsociety.ac.uk/help/training/creating-tailored-weights/ . I suggest you listen to the first video to decide whether you want to create your own weights.
Hope this helps,
Olena