Is that correct?ģ) If my understanding of point 2) (above) is correct, am I right that 'a_indinus_xw' is the only weight I have to use in my model? That is, that I don't have to use the cross-section weight for each and every single wave (i.e., waves 2, 3, 4, 5, 6, 7, and 8).Ĥ) In the exchange you had with Ewan (see link above) you spoke of 'scaling the data'. that I want to run a weighted model on an unbalanced dataset rather than on a balanced dataset) is that I can use the cross-section weight of the earliest wave in my dataset (in this case wave 1) and apply that weight to all pidps across all waves?Ģ) If so, am I right that this weight would be 'a_indinus_xw' given that I am looking at wave 1 to wave 8? That means that if I was looking at wave 2 to wave 8, the weight to be applied would be 'b_indinub_xw'. I have gone through the online discussion forum, notably the exchange you had with Ewan 4 years ago ( ), and I wanted to make sure I understood your advice correctly.ġ) Have I understood correctly that a possible remedy to my situation ( i.e. This is because by using a balanced panel dataset I end up losing nearly 2/3rd of my observations and given the sub-groups I am interested in I am ending up with too few observations which is generating imprecise coefficients and too large standard errors/confidence intervals. However, I don't want to run my analysis on a balanced panel dataset - but instead I want to run my model on an unbalanced dataset. My dataset is unbalanced.Īs I understand it I can only use the weights UKHLS provide to undertake analysis on a balanced panel dataset. I am using Stata 15.1 to run my multilevel model. My focus is on individuals (indresp file) who are aged between 16-64 and who completed a full interview (ivfio =1 ). ![]() The model is a two level logistic regression with observations (level 1) nested within individuals (level 2). I am undertaking a longitudinal data analysis using wave 1 to wave 8 of UKHLS (I am using all waves - i.e., wave 1, 2, 3, 4, 5, 6, 7 & 8).
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