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.