stabwtlong: Calculating stabilized weights for IPW analysis: Longitudinal...

In rqlm: Modified Poisson Regression for Binary Outcome and Related Methods

Calculating stabilized weights for IPW analysis: Longitudinal data

Description

This function calculates stabilized weights for IPW analysis of longitudinal data using logistic regressions. Both of untruncated and utruncated weights are provided.

Usage

stabwtlong(formula_denom, formula_num, data, trunc=c(0.01,0.99), digits=4)

Arguments

formula_denom	An object of class "formula" (or one that can be coerced to that class): a symbolic description of the denominator logistic regression model to be fitted.
formula_num	An object of class "formula" (or one that can be coerced to that class): a symbolic description of the numerator logistic regression model to be fitted.
data	A data frame, list or environment (or object coercible by as.data.frame to a data frame) containing the variables in the model.
trunc	Quantiles to be truncated the weights (default: 0.01, 0.99).
digits	Number of decimal places in the output (default: 4).

Value

Truncated and untruncated stabilized weights are calculated.

• sw1: Untruncated stabilized weights.

• sw2: Truncated stabilized weights.

References

Cole, S. R., and Hernan, M. A. (2008). Constructing inverse probability weights for marginal structural models. American Journal of Epidemiology 168, 656-664.

Westreich, D., Edwards, J. K., Lesko, C. R., Stuart, E., and Cole, S. R. (2017). Transportability of trial results using inverse odds of sampling weights. American Journal of Epidemiology 186, 1010-1014.

Examples

data(exdata04)

stabwtlong(formula_denom = A ~ L1 + L2 + L3, formula_num = A ~ L1, data = exdata04)

rqlm documentation built on Jan. 28, 2026, 9:07 a.m.