estimatr_glancers() R function from [estimatr]

Glance at an estimatr object


## S3 method for class 'lm_robust'
glance(x, ...)

## S3 method for class 'lh_robust'
glance(x, ...)

## S3 method for class 'iv_robust'
glance(x, ...)

## S3 method for class 'difference_in_means'
glance(x, ...)

## S3 method for class 'horvitz_thompson'
glance(x, ...)

Arguments

x: An object returned by one of the estimators
...: extra arguments (not used)

Returns

For glance.lm_robust, a data.frame with columns: - r.squared: 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.

adj.r.squared: the $R^2$ but penalized for having more parameters, rank
se_type: the standard error type specified by the user
statistic: the value of the F-statistic
p.value: p-value from the F test
df.residual: residual degrees of freedom
nobs: the number of observations used

For glance.lh_robust, we glance the lm_robust component only. You can access the linear hypotheses as a data.frame directy from the lh component of the lh_robust object

For glance.iv_robust, a data.frame with columns: - r.squared: The $R^2$ of the second stage regression

adj.r.squared: The $R^2$ but penalized for having more parameters, rank
df.residual: residual degrees of freedom
N: the number of observations used
se_type: the standard error type specified by the user
statistic: the value of the F-statistic
p.value: p-value from the F test
statistic.weakinst: 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.weakinst: p-value from the first-stage F test, a test of weak instruments; only reported if there is only one endogenous variable
statistic.endogeneity: 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.endogeneity: p-value from the F-test for endogeneity
statistic.overid: the value of the chi-squared statistic for the test of instrument correlation with the error term; only reported with overidentification
p.value.overid: p-value from the chi-squared test; only reported with overidentification

For glance.difference_in_means, a data.frame with columns: - design: the design used, and therefore the estimator used

df: the degrees of freedom
nobs: the number of observations used
nblocks: the number of blocks, if used
nclusters: the number of clusters, if used
condition2: the second, "treatment", condition
condition1: the first, "control", condition

For glance.horvitz_thompson, a data.frame with columns: - nobs: the number of observations used

se_type: the type of standard error estimator used
condition2: the second, "treatment", condition
condition1: the first, "control", condition

estimatr_glancers function

Glance at an estimatr object

Arguments

Returns

See Also