R: Modified Poisson Regression for Binary Outcome and Related Methods

# Modified Poisson Regression for Binary Outcome and Related Methods

## Documentation for package ‘rqlm’ version 4.3-2

- DESCRIPTION file
- Package NEWS

## Help Pages

rqlm-package | The 'rqlm' package.
bsci.ls | Calculating bootstrap confidence interval for modified least-squares regression based on the quasi-score statistic
bsci.pois | Calculating bootstrap confidence interval for modified Poisson regression based on the quasi-score statistic
coeff | Computation of the ordinary confidence intervals and P-values using the model variance estimator
exdata01 | A simulated example dataset
exdata02 | A simulated example dataset
exdata03 | A simulated example dataset with missing covariates
exdata04 | A simulated example dataset for target trial emulation
mch | A cluster-randomised trial dataset for the maternal and child health handbook
mi_glm | Multiple imputation analysis for the generalized linear model
mi_rqlm | Multiple imputation analysis for modified Poisson and least-squares regressions
qesci.ls | Calculating confidence interval for modified least-squares regression based on the quasi-score test
qesci.pois | Calculating confidence interval for modified Poisson regression based on the quasi-score test
qlogist | Augmented (modified) logistic regression analyses for estimating risk ratio
rqlm | Modified Poisson and least-squares regression analyses for binary outcomes
stabwt | Calculating stabilized weights for IPW analysis: Single time point
stabwtlong | Calculating stabilized weights for IPW analysis: Longitudinal data
stabwtmulti | Calculating stabilized weights for IPW analysis: Single time point (for more than 3 groups)
SumStat | Creating summary table for IPTW analysis using stabilized weights
ttemsm | Pooled logistic regression for target trial emulation