Augmented inverse probability weighted estimation and prediction for cause-specific proportional hazards regression with missing covariates
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DOI: 10.1080/02331888.2024.2343925
Abstract: This paper describes estimation of the regression parameters and prediction of the cumulative incidence functions under the cause-specific proportional hazards model when some of covariates are not fully observed. Assuming that missingness mechanism is missing… read more here.
Keywords: missing covariates; proportional hazards; regression; specific proportional ... See more keywords
Augmented inverse probability weighted estimation for conditional treatment effect
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DOI: 10.1080/10485252.2024.2377664
Abstract: The Augmented Inverse Probability Weighted (AIPW) estimation has been extensively studied in various scenarios across diverse research areas. This investigation explores the asymptotic properties of the AIPW estimator for the conditional average treatment effect. Under… read more here.
Keywords: probability weighted; treatment effect; inverse probability; augmented inverse ... See more keywords
Normalized Augmented Inverse Probability Weighting with Neural Network Predictions
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DOI: 10.3390/e24020179
Abstract: The estimation of average treatment effect (ATE) as a causal parameter is carried out in two steps, where in the first step, the treatment and outcome are modeled to incorporate the potential confounders, and in… read more here.
Keywords: augmented inverse; probability weighting; inverse probability; normalized augmented ... See more keywords