PPT-A quick intro to latent class and finite mixture modeling

Trang Quynh Nguyen May 9 2016 41068601 Advanced Quantitative Methods in the Social and Behavioral Sciences A Practical Introduction Objectives Provide a QUICK introduction to latent class models and finite mixture modeling with examples. Department of Economics. Stern School of Business. New York University. Latent Class Modeling. Outline. Finite mixture and latent class models . Extensions of the latent class model. Applications of several variations. Department of Economics. Stern School of Business. New York University. Some Applications of . Latent Class Modeling. In Health Economics. . Daniel . Oberski. Dept. of Methodology & Statistics . Tilburg University, The Netherlands. (with material from Margot . Sijssens-Bennink. & . Jeroen. . Vermunt. ). About Tilburg University Methodology & Statistics. Latent Classes. A population contains a mixture of individuals of different types (classes). Common form of the data generating mechanism within the classes. Observed outcome y is governed by the . common process . Part II: Definition and Properties. Nevin. L. Zhang. Dept. of Computer Science & Engineering. The Hong Kong Univ. of Sci. & Tech.. http://www.cse.ust.hk/~lzhang. AAAI 2014 Tutorial. Part II: Concept . Daniel Lee. Presentation for MMM conference . May 24, 2016. University of Connecticut. 1. 2. Introduction: Finite Mixture Models. Class of statistical models that treat group membership as a latent categorical variable. McLachlan, G., & Peel, D. (2001). . Finite mixture models. . New York: Wiley.. Murphy, K. P. (2013). . Machine learning: a probabilistic perspective. . Cambridge, Mass.: MIT Press.. Bishop, C. M. (2013). . William Greene. Stern School of Business. New York University. Part 6. Modeling Latent Parameter Heterogeneity. Parameter Heterogeneity. Fixed and Random Effects Models. Latent common time invariant “effects”. October 28, 2016. Objectives. For you to leave here knowing…. What is the LCR model and its underlying assumptions?. How are LCR parameters interpreted?. How does one check the assumptions of an LCR model?. Latent Classes. A population contains a mixture of individuals of different types (classes). Common form of the data generating mechanism within the classes. Observed outcome y is governed by the . common process . William Greene. Stern School of Business. New York University. New York NY USA. 4.2 . Latent Class Models. Concepts. Latent Class. Prior and Posterior Probabilities. Classification Problem. Finite Mixture. University of Lugano, Switzerland. May 27-31, . 2019. William Greene. Department of Economics. Stern School of . Business. New York University. 2B. Heterogeneity: Latent Class and Mixed Models. Agenda for 2B. Nevin. L. Zhang. Dept. of Computer Science & Engineering. The Hong Kong Univ. of Sci. & Tech.. http://www.cse.ust.hk/~lzhang. AAAI 2014 Tutorial. Part II: Concept . and Properties. Latent . Tree . A Gentle Introduction…. Hopefully. Angela B. Bradford, PhD, LMFT. School of Family Life. Brigham Young University. Background. Mixture Models (aka “finite mixture models”)- Models based on the idea that there are multiple characteristically different sub-populations within the population, and that those subpopulations are not directly observable. Mixture models characterize and estimate parameters for those sub-populations.