# Glance at an estimatr object

Glance at an estimatr object

# S3 method for lm_robust glance(x, ...) # S3 method for lh_robust glance(x, ...) # S3 method for iv_robust glance(x, ...) # S3 method for difference_in_means glance(x, ...) # S3 method for horvitz_thompson glance(x, ...)

## Arguments

x | An object returned by one of the estimators |
---|---|

... | extra arguments (not used) |

## Value

For `glance.lm_robust`

, a data.frame with columns:

the \(R^2\), $$R^2 = 1 - Sum(e[i]^2) / Sum((y[i] - y^*)^2),$$ where \(y^*\) is the mean of \(y[i]\) if there is an intercept and zero otherwise, and \(e[i]\) is the ith residual.

the \(R^2\) but penalized for having more parameters, `rank`

the standard error type specified by the user

the value of the F-statistic

p-value from the F test

residual degrees of freedom

the number of observations used

The \(R^2\) of the second stage regression

The \(R^2\) but penalized for having more parameters, `rank`

residual degrees of freedom

the number of observations used

the standard error type specified by the user

the value of the F-statistic

p-value from the F test

the value of the first stage F-statistic, useful for the weak instruments test; only reported if there is only one endogenous variable

p-value from the first-stage F test, a test of weak instruments; only reported if there is only one endogenous variable

the value of the F-statistic for the test of endogeneity; often called the Wu-Hausman statistic, with robust standard errors, we employ the regression based test

p-value from the F-test for endogeneity

the value of the chi-squared statistic for the test of instrument correlation with the error term; only reported with overidentification

p-value from the chi-squared test; only reported with overidentification

the design used, and therefore the estimator used

the degrees of freedom

the number of observations used

the number of blocks, if used

the number of clusters, if used

the second, "treatment", condition

the first, "control", condition

the number of observations used

the type of standard error estimator used

the second, "treatment", condition

the first, "control", condition

## See also

`generics::glance()`

, `estimatr::lm_robust()`

, `estimatr::lm_lin()`

, `estimatr::iv_robust()`

, `estimatr::difference_in_means()`

, `estimatr::horvitz_thompson()`