After the pseudo population dataset was generated, we apply outcome models on the pseudo population as-if the dataset is from a randomized experiment.
We propose three types of outcome models using parametric, semi-parametric and non-parametric approaches, respectively.
estimate_pmetric_erf estimates the hazard ratios using a parametric regression model. By default, call
gnm library to implement generalized nonlinear models.
estimate_semipmetric_erf estimates the smoothed exposure-response function using a generalized additive model with splines. By default, call
gam library to implement generalized additive models.
estimate_npmetric_erf estimates the smoothed exposure-response function using a kernel smoothing approach. By default, call
KernSmooth library to implement local polynomial fitting with a kernel weight. We use a data-driven bandwidth selection.