Statistical Analysis: Post Estimation Analysis

Retained estimation results (all accessible by name in subsequent operations)

• Coefficient vector
• Asymptotic covariance matrix
• Ancillary parameter vectors
• Predicted values
• Residuals or generalized residuals
• Log likelihood and other scalar statistics

Marginal effects for all models

List predictions with confidence intervals and residuals

Extrapolate predictions to out of sample values

Analysis of coefficients, linear combinations and nonlinear functions, standard errors and test statistics

Hypothesis tests

• Likelihood ratio tests
• LM tests
• Wald tests
• Nonnested: PE, J, Cox
• Vuong tests

Two step estimation and corrected covariance matrices