This is the repository for the English version of the Future Elderly Model, originally developed at the Leonard D. Schaeffer Center for Health Policy and Microsimulation.
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Check difference between core and self-completion samples, identify any bias #85
Alcohol consumption is only asked in the self-completion questionnaire from wave 4 onwards (where the good data on this is). We need to check that this is not introducing too much bias, or at least be aware of what bias it does introduce. From very quick checks, response to the self-completion questionnaire is higher for younger age groups, higher education levels, married people, healthier people (srh of Good to Excellent), and non-disabled (anyadl == 0). We need to get a good idea of the bias involved so would probably be good to make an R Notebook detailing the differences between the core and self-completion samples.
[ ] Make R Notebook to highlight differences between the core and self-completion samples and therefore the biases we could be introducing using this data.
Self-completion vs Core
Alcohol consumption is only asked in the self-completion questionnaire from wave 4 onwards (where the good data on this is). We need to check that this is not introducing too much bias, or at least be aware of what bias it does introduce. From very quick checks, response to the self-completion questionnaire is higher for younger age groups, higher education levels, married people, healthier people (srh of Good to Excellent), and non-disabled (anyadl == 0). We need to get a good idea of the bias involved so would probably be good to make an R Notebook detailing the differences between the core and self-completion samples.
Examples of subgroups to check:
_Originally posted by @ld-archer in https://github.com/ld-archer/E_FEM/issues/79#issuecomment-970367200_