Understanding Society User Support

Dear colleagues,

I'm a post-doc research associate at the University of Manchester. We're currently planning an analysis investigating how mental health problems spread within a family network using your data (thank you for providing such an excellent dataset!). However, we're confused about how to create the correct weighting on our data even after reading all the tutorial materials. So I sincerely hope we can have your support for our analysis. I will first brief you on our initial analytical plan:

1. Formulate an initial participant pool consisting of all data in waves 1, 3, 5, 7, 9, and 11, because the Strengths and Difficulties Questionnaire (SDQ) data are available in those waves.
2. Within this initial pool, compare the data quality for each family across the waves (e.g. compare the quality of SDQ data for family A in waves 1, 3, 5, 7, 9, and 11).
3. Select a particular dataset for each family if the dataset has the fewest missing values across the waves, and formulate a large cross-sectional dataset. For example, if SDQ data have the fewest missing values for family A in wave 1, and for family B in wave 3, we use data for family A from wave 1, and data for family B from wave 3 to formulate a cross-sectional dataset.

By doing so, we hope we can boost our sample size and the quality of the data. This is because our analytical approach (network analysis) requires highly on data quality. However, we're aware that this participant selection approach may introduce bias. Therefore, we're wondering whether you can suggest whether our participant selection plan is reasonable in the light of your research design, and if so, what materials we can use to create the correct weighting values for our data?

Thank you in advance for your time and help, and we're looking forward to hearing from you.

Kind regards,
Yushi