An S3method for sandwich::estfun for producing a matrix of contributions
to the direct adjustment estimating equations.
Value
An \(n\times 2\) matrix of empirical estimating equations for the direct adjustment model fit. See Details for definition of \(n\).
Details
If a prior covariance adjustment model has
been passed to the offset argument of the teeMod model
using cov_adj(), estfun.teeMod() incorporates
contributions to the estimating equations of the covariance adjustment model.
The covariance adjustment sample may not fully overlap with the direct
adjustment sample, in which case estfun.teeMod() returns a
matrix with the same number of rows as the number of unique units of observation
used to fit the two models. Uniqueness is determined by matching units of
assignment used to fit the covariance adjustment model to units of assignment
in the teeMod model's Design slot; units of observation
within units of assignment that do not match are additional units that add
to the row count.
Theby argument in cov_adj() can provide a column or a pair of
columns (a named vector where the name specifies a column in the direct
adjustment sample and the value a column in the covariance adjustment
sample) that uniquely specifies units of observation in each sample. This
information can be used to align each unit of observation's contributions
to the two sets of estimating equations. If no by argument is
provided and units of observation cannot be uniquely specified, contributions
are aligned up to the unit of assignment level. If standard errors are
clustered no finer than that, they will provide the same result as if each
unit of observation's contributions were aligned exactly.