Michael Seltzer
Associated IES Content
Grant
Non-Linear Multilevel Latent Variable Modeling with a Metropolis-Hastings Robbins-Monro Algorithm
The goal of this project was to bring together the benefits of multilevel modeling and latent variable modeling. To do so, the project proposed a flexible nonlinear multilevel latent variable modeling framework under which: (1) random effects and latent variables are treated synonymously because both represent unobserved heterogeneity; (2) a nonlinear random effect regression model permits the specification and testing of important structural relations (e.g. mediation or moderation effects) ...
Federal funding program:
Award number:
R305D100039
FY2010 IES Peer Reviewers
FY2010 IES Research Peer Review Panel
FY2009 IES Peer Reviewers
FY2009 IES Research Peer Review Panel
FY2006 IES Peer Reviewers
FY2006 IES Peer Reviewers