A latent class analysis (LCA) of the BiBBS cohort

Latent class analysis (LCA) is a statistical method that allows us to identify subgroups in a population that we have not measured. It identifies patterns of similar responses in measure such as questionnaires, and groups individuals based on these. This can allow us to better understand complex and diverse populations.

In my PhD thesis (completed December 2023), I found that LCA could be used to group women in the interim BiBBS birth cohort based on their responses to questions around social positions and identities such as ethnicity, English language ability and measures of socio-economic status. This work extends that analysis to the full BiBBS dataset and explores how latent groups relate to different outcomes.