Model Estimation and Data Analysis: Ordered Choice Models

Ordered choice model analysis using LIMDEP and NLOGIT

LIMDEP and NLOGIT offer extensive capabilities for ordered choice analysis including ordered probit, logit and hierarchical models, zero inflation models, partial effects, panel data and more.

Ordered Choice Model Types

  • Ordered probit, logit
  • Generalized ordered probit and logit
  • Partial effects
    • Standard errors computed by the delta method or Krinsky and Robb
    • Partial effects for discrete variables
    • Transition matrices
  • Restrictions
    • Wald, LM, LR tests
    • Linear restrictions
  • Predictions
  • Heteroscedasticity
    • LR and LM test
    • Maximum likelihood estimation
  • Censored data
  • Stratification
  • Choice based sampling
  • Robust covariance matrix, sandwich, cluster
  • Sample selection model
    • Maximum likelihood ordered probit with selection
    • Ordered probit selection criterion
  • Panel data
    • Fixed effects
    • Random effects
    • Random parameters
    • Latent class
  • Discrete hazard model, ordered extreme value
  • Hierarchical ordered probit - heterogeneous thresholds
  • Zero inflated ordered probit; endogenous zero inflation
  • Bivariate ordered probit