FMM: PREFIX FOR FINITE MIXTURE MODELS

• Mixtures of regression models
• Mixtures of distributions
• With two, three, four, or more latent classes (components)

OUTCOME TYPES

• Continuous, modeled as
• Linear
• Truncated
• Interval
• Tobit
• Instrumental variables
• Binary, modeled as
• Logistic
• Probit
• Complementary log-log
• Count, modeled as
• Poisson
• Negative binomial
• Truncated Poisson
• Categorical, modeled as
• Multinomial logistic
• Ordinal, modeled as
• Ordered logistic
• Ordered probit
• Survival, modeled as
• Exponential
• Weibull
• Lognormal
• Loglogistic
• Gamma
• Fractional, modeled as
• Beta
• Generalized linear models (GLMs)
• 11 families: Gaussian, Bernoulli, beta, binomial, Poisson, negative binomial, exponential, gamma, lognormal, loglogistic, Weibull
• 5 links: identity, log, logit, probit, complementary log-log
• Mixtures of above models
• Mixtures of above models with a point mass at a single value

MODEL CLASS MEMBERSHIP

• Predictors of class membership
• Multinomial logistic model

STARTING VALUES

• EM algorithm
• Fixed or random starting values
• Select number of random draws

INFERENCES

• Expected means, probabilities, or counts in each class
• Expected proportion of population in each class
• AIC and BIC information criteria
• Wald tests of linear and nonlinear constraints
• Likelihood-ratio tests
• Contrasts
• Pairwise comparisons
• Linear and nonlinear combinations of coefficients with SEs and CIs

PREDICTIONS

• Class membership
• Posterior class membership
• Predicted means, probabilities, counts
• For each latent class
• Marginal with respect to latent classes
• Marginal with respect to posterior latent classes
• Survivor function
• Density function
• Distribution function

POSTESTIMATION SELECTOR

• View and run all postestimation features for your command
• Automatically updated as estimation commands are run

FACTOR VARIABLES

• Automatically create indicators based on categorical variables
• Form interactions among discrete and continuous variables
• Include polynomial terms
• Perform contrasts of categories/levels
Watch Introduction to Factor Variables in Stata tutorials

MARGINAL ANALYSIS

• Estimated marginal means
• Marginal and partial effects
• Average marginal and partial effects
• Adjusted predictions, means, and effects
• Works with multiple outcomes simultaneously
• Contrasts of margins
• Pairwise comparisons of margins
• Profile plots
• Graphs of margins and marginal effects