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(Internal) Estimate components of the sandwich covariance matrix returned by vcov_tee()

Usage

.get_a22_inverse(x, ...)

.get_a11_inverse(x)

.get_a21(x)

.get_tilde_a22_inverse(x, ...)

.get_tilde_a21(x)

Arguments

x

a fitted teeMod model

...

arguments passed to bread method

Value

.get_a22_inverse()/.get_tilde_a22_inverse(): A \(2\times 2\) matrix corresponding to an intercept and the treatment variable in the direct adjustment model

.get_a11_inverse(): A \(p\times p\) matrix where \(p\) is the dimension of the covariance adjustment model, including an intercept

.get_a21()/.get_tilde_a21(): A \(2\times p\) matrix where the number of rows are given by the intercept and the treatment variable in the direct adjustment model, and the number of columns are given by the dimension of the covariance adjustment model

Details

.get_a22_inverse()/.get_tilde_a22_inverse(): \(A_{22}^{-1}\) is the "bread" of the sandwich covariance matrix returned by vcov_tee() whether one has fit a prior covariance adjustment model or not.

.get_a11_inverse(): \(A_{11}^{-1}\) is the "bread" of the sandwich covariance matrix for the covariance adjustment model. This matrix contributes to the meat matrix of the direct adjustment sandwich covariance matrix.

.get_a21()/.get_tilde_a21(): \(A_{21}\) is the gradient of the estimating equations for the direct adjustment model taken with respect to the covariance adjustment model parameters. This matrix is the crossproduct of the prediction gradient for the units of observation in \(\mathcal{Q}\) and the model matrix of the direct adjustment model.