Hypothesis testing

• Wald test for linear constraints
• Wald test (delta method) for nonlinear constraints
• Likelihood-ratio test after any ML estimation
• Bonferroni, Holm, and Šidák adjustments for multiple comparisons*

Generalized testing

• ability to combine seperate estimates into single combined estimates
• robust covariance matrix of combined estimates
• tests of linear and nonlinear combinations of estimates across estimated models
• point estimates and confidence intervals of linear and nonlinear combinations of estimates across estimated models

Predictions

• ability to obtain predicted values after all estimation commands
• predictor types are tightly coupled to the estimation command

Generalized Predictions

• linear and nonlinear combinations of
• standard predictions
• equation index values
• estimated coefficients
• data
• Inferential statistics for generalized predictions
• point estimates
• standard errors
• variance
• Wald test statistic
• significance levels
• point-wise confidence intervals

Postestimation statistics

• estimation sample summary statistics*
• Akaike and Bayesian information criteria*
• covariance matrix analysis

Adjusted predictions

• predicted values or probabilities
• predictions adjusted to set levels of regressors
• predictions adjusted to set levels of covariates
• predictions adjusted to set levels of terms

Hausman test

• test the independence of irrelevant alternative (IIA) after
  • multinomial logit
  • conditional logistic regression
• tests exogeneity or over-identifying restrictions for
• two-stage least squares (2SLS)
• three-stage least squares (3SLS)

Point estimates for combinations of coefficients

• odds ratios
• standard errors
• test statistics

Marginal effects

• marginal effects and elasticities
• standard errors and confidence intervals
• computation of effects at means or specified covariate values
• computation of effects for any predicted statistic

Save and restore estimation results

Nonlinear combinations of coefficients

• point estimates
• standard errors
• t and Z statistics
• p-values
• confidence intervals
• covariances between combinations
• supports survey and clustered data