mcee_config_glm: Configure GLM for MCEE nuisance parameters

In MRTAnalysis: Assessing Proximal, Distal, and Mediated Causal Excursion Effects for Micro-Randomized Trials

Configure GLM for MCEE nuisance parameters

Description

Creates a configuration to fit nuisance parameters using generalized linear models via stats::glm().

Usage

mcee_config_glm(target, formula, family = NULL, clipping = NULL)

Arguments

target	Character. Nuisance parameter name ("p", "q", "eta", "mu", "nu").
formula	RHS-only formula (e.g., ~ X1 + X2 + poly(time, 2)).
family	Optional GLM family. Defaults to binomial() for "p"/"q", gaussian() for "eta"/"mu"/"nu".
clipping	Optional numeric vector c(lo, hi) to clip predictions into [lo, hi] for numerical stability.

Value

A configuration list for use with mcee_general.

Examples

# Binary outcome model for propensity
cfg_q <- mcee_config_glm("q", ~ dp + M, family = binomial())

# Gaussian outcome model
cfg_eta <- mcee_config_glm("eta", ~ dp + X1)

MRTAnalysis documentation built on Sept. 9, 2025, 5:41 p.m.