Statistical Methods for Handling Incomplete Data

By Jae Kwang Kim, Jun Shao. 2013

195 citations recorded by the source corpus.

Introduction Introduction Outline How to Use This Book Likelihood-Based Approach Introduction Observed Likelihood Mean Score Approach Observed Information Computation Introduction Factoring Likelihood Approach EM Algorithm Monte Carlo Computation Monte Carlo EM Data Augmentation Imputation Introduction Basic Theory for Imputation Variance Estimation after Imputation Replication Variance Estimation Multiple Imputation Fractional Imputation Propensity Scoring Approach Introduction Regression Weighting Method Propensity Score Method Optimal Estimation Doubly Robust Method Empirical Likelihood Method Nonparametric Method Nonignorable Missing Data Nonresponse Instrument Conditional Likelihood Approach Generalized Method of Moments (GMM) Approach Pseudo Likelihood Approach Exponential Tilting (ET) Model Latent Variable Approach Callbacks Capture-Recapture (CR) Experiment Longitudinal and Clustered Data Ignorable Missing Data Nonignorable Monotone Missing Data Past-Value-Dependent Missing Data Random-Effect-Dependent Missing Data Application to Survey Sampling Introduction Calibration Estimation Propensity Score Weighting Method Fractional Imputation Fractional Hot Deck Imputation Imputation for Two-Phase Sampling Synthetic Imputation Statistical Matching Introduction Instrumental Variable Approach Measurement Error Models Causal Inference Bibliography Index

Subfields: Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/91cf60225508a84853f1f5d8664f80732e123676

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Statistics and Probability

  1. Kosuke Morikawa
  2. Yutaka Kano
  3. Peng Ding
  4. Shu Yang
  5. Linbo Wang
  6. Jae Kwang Kim
  7. Xinran Li
  8. Kevin Guo

Citations in the corpus