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 separate estimates into single combined estimate
- robust covariance matrix of combined estimates
- tests of linear and nonlinear combinations of estimates across fitted models
- point estimates and confidence intervals of linear and nonlinear
combinations of estimates across fitted models
Predictions
- ability to obtain predicted values after all estimation commands
- predictor types that are tightly coupled to the estimation command
- default predicted value that is most relevant to the fitted model
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 statistics
- significance levels
- pointwise confidence intervals
Postestimation statistics
- estimation sample summary statistics
- Akaike and Bayesian information criteria
- covariance matrix analysis
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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
- test exogeneity or overidentifying 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
- support for survey and clustered data
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