Package: qgcompint 1.0.2

Table of Contents | Introduction | The model | Basics: fitting a model with a modifier | Basics: getting bounds for pointwise comparisons | Basics: plotting weights (weights are at referent level of modifier) | Basics: bootstrapping | Plotting bootstrapped fits (plotting predictions) | Overlay plots of predictions at multiple modifier levels | Basics: Estimating equations | Plotting predictions from estimating equation fits (plotting predictions) | Basics: categorical modifier, binary outcome | Simulated data defaults | The wrong way to include categorical modifiers | The right way to include categorical modifiers (use as.factor()) | Bounds for pointwise comparisons with categorical modifiers | Overlay plots of predictions at multiple modifier levels | Global tests of interaction for categorical modifiers | Basics: Non-numerical factor modifiers | Basics: Continuous modifiers | Stratified effects, weights, and pointwise effect comparisons at specific values of a continuous confounder | Non-linear fits | Survival analysis | Frequently asked questions | How does qgcomp/qgcompint address collinearity | Is there an upper limit in terms of the number of variables I can include? | Why are estimating equation methods and bootstrapping both used? Is one preferable? | Why isn't available in this package even though it is in the qgcomp package? | How do I use multiple modifiers? | See also | References | Original quantile g-computation paper | First paper to use qgcompint | Acknowledgments