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Support #2058

Using longitudinal weights when combining Covid-19 waves and mainstage waves of UKHLS

Added by James Laurence 3 months ago. Updated about 2 months ago.

Status:
Resolved
Priority:
Normal
Category:
Weights
Start date:
02/22/2024
% Done:

100%


Description

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

#1

Updated by Understanding Society User Support Team 3 months ago

  • Category set to Weights
  • Assignee changed from Understanding Society User Support Team to Olena Kaminska
#2

Updated by Olena Kaminska 3 months ago

James,

In short Covid weights are based on wave 9of the mainstage of UKHLS, so you can use them as they are for analysis of mainstage wave 9 and Covid data.

Nevertheless, if you use Covid data with previous information from other waves (wave 6-9, for example), you would need to account for additional missingness in these waves. It may not be large, so double check the proportion of missingness first. If it is substantial it is best to create a tailored weight. The base weight can be either a Covid weight or wave 6 mainstage weight.

Hope this helps,
Olena

#3

Updated by James Laurence 3 months ago

Hi Olena,

That's great. Thanks so much for the helpful insights.

Best wishes,

James

#4

Updated by Understanding Society User Support Team about 2 months ago

  • Status changed from New to Resolved
  • % Done changed from 0 to 100
  • Private changed from Yes to No

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