Recursive partitioning for monotone missing at random longitudinal markers

Missing data imputation, classification, prediction and average treatment effect estimation via Random Recursive Partitioning

In this paper we describe some applications of the Random Recursive Partitioning (RRP) method. This method generates a proximity matrix which can be used in non parametric hot-deck missing data imputation, classification, prediction, average treatment effect estimation and, more generally, in matching problems. RRP is a Monte Carlo procedure that randomly generates non-empty recursive partition...

Distinguishing "Missing at Random"i and "Missing Completely at Randomn"

Performance of weighted estimating equations for longitudinal binary data with drop-outs missing at random.

The generalized estimating equations (GEE) approach is commonly used to model incomplete longitudinal binary data. When drop-outs are missing at random through dependence on observed responses (MAR), GEE may give biased parameter estimates in the model for the marginal means. A weighted estimating equations approach gives consistent estimation under MAR when the drop-out mechanism is correctly ...

Fixed Effects Models for Longitudinal Binary Data with Drop-outs Missing at Random

We consider the problem of attrition under a logistic regression model for longitudinal binary data in which each subject has his own intercept parameter, and where parameters are eliminated via conditional logistic regression. This is a fixed-effects, subject-specific model which exploits the longitudinal data by allowing subjects to act as their own controls. By modeling and conditioning on t...

TECHNICAL REPORT Fixed effects models for longitudinal binary data with drop-outs missing at random

We consider the problem of attrition under a logistic regression model for longitudinal binary data in which each subject has his own intercept parameter, and those parameters are eliminated via conditional logistic regression. This is a fixed-effects, subject-specific model which exploits the longitudinal data by allowing subjects to act as their own controls. By modeling and conditioning on t...