Understanding Society User Support

Hi there,

I was just hoping to get some more advice regarding correctly weighting my analysis combining the mainstage and Covid-19 waves of the UKHLS. You kindly helped with a previous weighting issue I had for treating the data as repeated cross-sections. However, I am also hoping to conduct some fixed effects panel data analysis of the combined mainstage and Covid-19 waves (web survey only).

As a basic set-up, I am combining wave 9 of the UKHLS mainstage survey (the last mainstage survey that doesn’t cover the pandemic) with waves 1 to 9 of the COVID-19 survey. The data are in long format. As I would like to do some fixed effects longitudinal analysis, I believe I need to use the longitudinal weights. From my reading, I need to choose the longitudinal weight from the last wave of the survey I will be using – in this case wave 9 of the Covid-19 survey: ci_betaindin_lw

Applying this weight [ci_betaindin_lw] will give me a balanced panel, restricting the sample to everyone who participated in all 9-waves of the Covid-19 survey. However, I would also like to analyse wave 9 of the mainstage survey as part of a longitudinal, fixed effects analysis covering mainstage wave 9 and Covid survey waves 1-9. Is this possible? If so, is one approach to feed back the ci_betaindin_lw weight so that the people who were in wave 9 of the mainstage survey who were also present in all 9-waves of the Covid-19 survey have the weight value of ci_betaindin_lw? Therefore, the ci_betaindin_lw weight would cover the mainstage wave 9 sample and the Covid-19 sample.

In case it’s not clear, to make-up an example of the data in long-format, which contains wave 9 of the mainstage survey and waves 1-9 of the Covid survey. Pidp no. 111111 was present in wave 9 of the mainstage sirvey and all 9 waves of the Covid survey and had a value of 1.5 for their longitudinal weight at wave 9 of the covid survey (ci_betaindin_lw). So, my data would just look like this:

[PIDP] [WAVE] [Value of ci_betaindin_lw]
111111 Mainstage wave 9 Missing Value
111111 COVID wave 1 1.5
111111 COVID wave 2 1.5
111111 COVID wave 3 1.5
111111 COVID wave 4 1.5
111111 COVID wave 5 1.5
111111 COVID wave 6 1.5
111111 COVID wave 7 1.5
111111 COVID wave 8 1.5
111111 COVID wave 9 1.5

Is just feeding back the value of ci_betaindin_lw (1.5) what I need to do? So, it would now look like:

[PIDP] [WAVE] [Value of ci_betaindin_lw]
111111 Mainstage wave 9 1.5
111111 COVID wave 1 1.5
111111 COVID wave 2 1.5
111111 COVID wave 3 1.5
111111 COVID wave 4 1.5
111111 COVID wave 5 1.5
111111 COVID wave 6 1.5
111111 COVID wave 7 1.5
111111 COVID wave 8 1.5
111111 COVID wave 9 1.5

If so, could this method apply if I wanted to include more mainstage waves of data? So, if I wanted to include waves 6, 7, 8 and wave 9 of the mainstage survey alongside waves 1-9 of the Covid survey - would I just feed back an individuals' weight value for ci_betaindin_lw back so the individual have that weight value for mainstage waves, 6, 7, 8 and 9?

I may be completely misunderstanding how to use the longitudinal weights, or have missed something crucial meaning you can't applying the Covid longitudinal weights to the pre-Covid survey mainstage waves. If so, apologies in advance and any advice would be hugely appreciated.

Best wishes,

James