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NMMIPW (version 0.1.0)

Inverse Probability Weighting under Non-Monotone Missing

Description

We fit inverse probability weighting estimator and the augmented inverse probability weighting for non-monotone missing at random data.

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Version

Install

install.packages('NMMIPW')

Monthly Downloads

200

Version

0.1.0

License

GPL (>= 2)

Maintainer

Andrew Ying

Last Published

December 20th, 2021

Functions in NMMIPW (0.1.0)

link_func_grad

This function computes the gradient of our link function that respects the positivity
link_func_grad_vec

This function vectorizes link_func_grad
regress_fit

This function returns the residuls after fiting a func regression, where func is the user-specified function
summary.NMMIPW

Summarizing IPW or AIPW Estimators under Nonmonotone Missing at Random Data
PS

This function prepares necessary list of information for fitting IPW or AIPW
link_func_vec

This function vectorizes link_func
link_func

This function computes our link function that respects the positivity
nmm_fit

Fitting IPW or AIPW Estimators under Nonmonotone Missing at Random Data
nmm_preprocessing

This function prepares the user-provided data into the correct format
prop_compute

This function computes propensities of entries being fully observed