Abstract.In this article,we describe lclogit ,a Stata command for fitting a discrete-mixture or latent-class logit model via the expectation-maximization algorithm.Keywords:st0312,lclogit,lclogitpr,lclogitcov,lclogitml,latent-class model,ex- pectation-maximization algorithm,mixed logit 1...
(2003). Bayesian inference and model selection in latent class logit models with parameter constraints: an application to market segmentation. Journal of Applied Statistics 30, 191-204.Oh, M.-S., Choi, J.W., Kim, D.-G.: Bayesian inference and model selection in latent class logit models ...
In subject area: Social Sciences A Latent Class Model is a statistical modeling technique that incorporates categorical latent variables, instead of continuous latent variables, to identify distinct subgroups or categories of individuals within a population. This approach is particularly useful in the anal...
Like its predecessor, lclogit2 uses the Expectation-Maximization (EM) algorithm to estimate latent class conditional logit (LCL) models. But it executes the EM algorithm's core algebraic operations in Mata, and runs considerably faster as a result. It also allows linear constraints on parameters ...
Sign in to download hi-res image Fig. 4. Growth Mixture Modeling (GMM). k latent classes are estimated, each having class-specific growth parameters. In GMM, any part of the model can be class-specific (including the means and variances of the latent growth parameters, the indicator varianc...
First, it creates the variables to be used as “predictors” in the scoring equations. For ordinal and continuous indicators, these are copies of the variables in the data set, and for categorical variables, these are dummies for the response categories. In addition, dummies are created for mi...
LLCA, for Located Latent Class Analysis, estimates probit unidimensional latent class models, as described in Uebersax (1993). This is a discrete latent trait model, similar to the logistic unidimensional latent class (e.g., Lindsay, Clogg, and Grego, 1991), but based on a probit, rather...
in R Y6 Y5 Y4 Y3 Y2 0.1045 0.4535 Classes; population share Daniel Tompsett/LCA in R and STATA Y1 0.442 9/29 Step 1 in STATA In STATA we can fit the LCM with the gsem command gsem(Y1-Y6<-), logit lclass(class 3) nolog The posterior probabilities of belonging to each class ...
Latent Class Analysis is a statistically principled technique for unsupervised learning that uses a probability model to infer relationships between observed categorical data and unmeasured variables. It identifies latent classes that explain the observed patterns in the data, allowing for analysis and clas...
Using this practice, a discrete choice model and a latent variables or a latent class model can be considered simultaneously. Latent class multinomial logit (LC-MNL) models have been used to capture taste heterogeneity by modeling latent population segments that differ in their mode choice ...