# View in a new page

From InterSciWiki

- h[1] DependVarb Description of dependent variable
- h[2] URmodel Coefficient estimates from the unrestricted model (includes standardized coefficients and VIFs). Two pvalues are given for H0: β=0. One is the usual pvalue, the other (hcpval) is heteroskedasticity consistent. If stepkept=TRUE, the table will also include the proportion of times a variable is retained in the model using stepwise regression.
- h[3] Rmodel Coefficient estimates from the restricted model. If relaimp=TRUE, the R2 assigned to each independent variable is shown here.
- h[4] EndogeneityTests Hausman tests (H0: variable is exogneous), with F-statistic for weak instruments (a rule of thumb is that the instrument is weak if the F-stat is below 10), and Sargan test (H0: instrument is uncorrelated with second-stage 2SLS residuals).
- h[5] Diagnostics Regression diagnostics for the restricted model: RESET test (H0: model has correct functional form); Wald test (H0: appropriate variables dropped); Breusch-Pagan test (H0: residuals homoskedastic; Shapiro-Wilkes test (H0: residuals normal); Hausman test (H0: Wy is exogenous); Sargan test (H0: residuals uncorrelated with instruments for Wy). If slmtests=TRUE, the LaGrange multiplier tests (H0: spatial lag term not needed) are reported here.
- h[6] OtherStats Other statistics: Composite weight matrix weights (see details); R2 for restricted model and unrestricted model; number of imputations; number of observations; Fstat for weak instruments for Wy.
- h[7] DescripStats Descriptive statistics for variables in unrestricted model.
- h[8] totry Character string of variables that were most significant in the unrestricted model as well as additional variables that proved significant using the add1 function on the restricted model.
- h[9] didwell Character string of variables that were most significant in the unrestricted model.
- h[10] dfbetas Influential observations for dfbetas (see details)
- h[11] data Data as used in the estimations: Wy xW, aa (imputed variables), etc. These can be used in Bayesian, Path analysis, and Pearl's causal graph adjustments.
- Back to Visual Manual