3 critical issues regarding COVID-19 UK Household Longitudinal Dataset
Dear UCL Institute of Education,
I am Seung Un Lee, currently studying Master's of Urban Economics at the National University of Singapore. I have a few critical issues regarding UK longitudinal studies - Covid19 dataset that your institution collects and provides and I was hoping if you could clarify it. Before that, I want to say thank you on behalf of our research team, with Associate Professor Kwan Ok Lee (profile) and Assistant Professor Michael Mai (profile), as we are using this dataset for our research in finding a correlation between Mental Health and Covid 19 National Lockdown.
The issues are as follows:
First, your team has collected respondents' various long-term health conditions. However, the responses seemed to be incompatible along the waves. I have attached a datasheet of the "Mentioned" response ratio by each wave. As you can see, Wave 2 and Wave 3 are way off the pattern. (The values were extracted from the raw dataset and cross-checked from the CLOSER discovery website.) It seems pretty clear that there is a problem with the values, so is there any reason behind this fluctuation? and how can we alter this value to make it consistent along the waves? Is there any way we can fix it to use it in our research?
Second, our team is using the dataset collected from Wave 1 (April 2020) to Wave 8 (March 2021), but we are hoping if you could clarify the exact date of when the survey started and ended. This is to match the period of National Lockdown that was imposed 3 times, including the most recent one in January, so that we can see how it affected the respondents' condition.
Third, we checked that there are two types of sampling weight, cX_betaindin_xw (cross-sectional) and cX_betaindin_lw (longitudinal). I tried to check the difference but the dictionary doesn't hold much information regarding these two variables. Can you please elaborate? We would be grateful if you could spare your time to give us a reply because the sampling weight issue is also another very important factor for our research and the dataset credibility.
Thank you again so much, and I will be looking forward to receiving any comments from you all! A bit late but, Happy New Year and hope you have a wonderful day :)
Sincerely, Seung Un.