dot-align_and_extend_estfuns: (Internal) Align the dimensions and rows of direct adjustment...

In propertee: Standardization-Based Effect Estimation with Optional Prior Covariance Adjustment

(Internal) Align the dimensions and rows of direct adjustment and covariance adjustment model estimating equations matrices

Description

(Internal) Align the dimensions and rows of direct adjustment and covariance adjustment model estimating equations matrices

Usage

.align_and_extend_estfuns(x, ctrl_means_ef_mat = NULL, by = NULL, ...)

Arguments

x	a fitted teeMod model
ctrl_means_ef_mat	optional, a matrix of estimating equations corresponding to the estimates of the marginal (and possibly conditional) means of the outcome and offset in the control condition. These are aligned and extended in the same way as the matrix of estimating equations for x and cbinded to them
by	optional, a character vector indicating columns that uniquely identify rows in the dataframe used for fitting x and the dataframe passed to the data argument of the covariance adjustment model fit. The default is NULL, in which case the unit of assignment columns specified in the StudySpecification slot of x are used.
...	mostly arguments passed to methods, but the special case is the argument loco_residuals, which indicates the offsets in the residuals of x should be replaced by versions that use leave-one-cluster-out estimates of the covariance model

Details

.align_and_extend_estfuns() first extracts the matrices of contributions to the empirical estimating equations for the direct adjustment and covariance adjustment models; then, it pads the matrices with zeros to account for units of observation that appear in one model-fitting sample but not the other; finally it orders the matrices so units of observation (or if unit of observation-level ordering is impossible, units of assignment) are aligned.

Value

A list of two matrices, one being the aligned contributions to the estimating equations for the direct adjustment model, and the other being the aligned contributions to the covariance adjustment model.

propertee documentation built on Aug. 22, 2025, 1:09 a.m.