getScoreResidualsFromClogit: Get the (conditional) score residuals from conditional...
In drgee: Doubly Robust Generalized Estimating Equations

Description Usage Arguments Details Value Author(s) See Also

View source: R/conditFit.R

A function to obtain the conditional score residuals from conditional logistic regression as well as the sum of derivatives of these residuals with respect to the parameters evaluated at the estimated parameters.

1	getScoreResidualsFromClogit(fit, coefs, y, x, id)

`fit`	A fitted object. Could be any object that has a class.function `coefficients`, but is intended to be used with `clogit` in the `survival` package.
`coefs`	An estimate of the parameters. If the argument `fit` is supplied, this will be replaced by `coefficients(fit)`.
`y`	The observed outcomes.
`x`	The design matrix.
`id`	The cluster identification variable.

getScoreResidualsFromClogit calculates the residuals from the conditional score equations used in conditional logistic regression as we as the sums of their derivatives with respect to the paramaters.

This is useful if one wants to use a calculate the sandwich estimate of a variance where the uncertainty in the estimation of a conditional odds ratio needs to be taken into account.

getScoreResidualsFromClogit return a list containing:

`U`	An n x p matrix, where n is the number of observations and p is the length of the estimated parameter.
`dU.sum`	An p x p matrix containing the sums of the derivatives. The rows correspond to the estimating equations and the columns correspond to the partial derivatives.
`dU.mean`	The mean cluster sum of the derivatives of the score residuals from the conditional likelihood.