summary.opsr: Summarizing OPSR Model Fits

In OPSR: Ordinal Probit Switching Regression

Summarizing OPSR Model Fits

Description

Follows the convention that opsr does the bare minimum model fitting and inference is performed in summary.

Usage

## S3 method for class 'opsr'
summary(object, rob = TRUE, ...)

Arguments

object	an object of class "opsr".
rob	if TRUE, the sandwich::sandwich covariance matrix extimator is used.
...	further arguments passed to or from other methods.

Value

An object of class "summary.opsr". In particular the elements GOF, GOFcomponents and wald require further explanation:

GOF	Contains the conventional goodness of fit indicators for the full model. LL2step is the log-likelihood of the Heckman two-step solution (if the default starting values were used). LLfinal is the log-likelihood at final convergence and AIC, BIC the corresponding information critereon.
GOFcomponents	Contains the goodness of fit for the model components. LLprobit is the log-likelihood (LL) contribution of the ordinal probit model. LLprobitEl the LL of the "equally likely" and LLprobitMs the LL of the "market share" model. With these three metrics the pseudo R2 is computed and returned as pseudoR2el and pseudoR2ms. R2 reports the usual coefficient of determination (for the continuous outcomes jointly and for each regime separately).
wald	Contains the results of two Wald-tests as conducted with help of car::linearHypothesis. The two H0 hypothesis are 1. All coefficients of the explanatory variables are 0 and 2. The rho parameters (capturing error correlation) are zero.

OPSR documentation built on Nov. 1, 2024, 5:07 p.m.