Revision as of 20:15, 27 November 2020 edit Cewbot (talk \| contribs) Bots 8,374,605 edits m Fix broken anchor: 2020-11-27T19:45:07Z #Growth_analysis→Nonlinear mixed-effects model#Example: Growth analysis ← Previous edit		Revision as of 20:16, 27 November 2020 edit undo Cewbot (talk \| contribs) Bots 8,374,605 edits m Fix broken anchor: 2020-11-27T19:45:34Z #Disease_progression_modeling→Nonlinear mixed-effects model#Example: Disease progression modeling Next edit →
Line 25: ===Medicine=== Latent-variable methodology is used in many branches of [[medicine]]. A class of problems that naturally lend themselves to latent variables approaches are [[longitudinal studies]] where the time scale (e.g. age of participant or time since study baseline) is not synchronized with the trait being studied. For such studies, an unobserved time scale that is synchronized with the trait being studied can be modeled as a transformation of the observed time scale using latent variables. Examples of this include [[Nonlinear_mixed-effects_model#~~Disease_progression_modeling~~Example: Disease progression modeling\|disease progression modeling]] and [[Nonlinear_mixed-effects_model#Example: Growth analysis\|modeling of growth]] (see box). ==Inferring latent variables==

Latent and observable variables: Difference between revisions