Tsiatis, Anastasios A.

Semiparametric theory and missing data / Anastasios A. Tsiatis. - New York : Springer, c2006. - xvi, 383 p. : ill. ; 24 cm. - Springer series in statistics. .

Includes bibliographical references and index.

Introduction to semiparametric models --
Hilbert Space for random vectors --
The geometry of influence functions --
Semiparametric models --
Examples of semiparametric models --
Models and methods for missing data --
Missing and coarsening at random for semiparametric models --
The nuisance tangent space and its orthogonal complement --
Augmented inverse probability weighted complete-case estimators --
Improving efficiency and double robustness with coarsened data --
Locally efficient estimators for coarsened-data semiparametric models --
Approximate methods for gaining efficiency --
Double-robust estimator of the average causal treatment effect --
Multiple imputation: a frequentist perspective. Table of contents

This book summarizes current knowledge of the theory of estimation for semiparametric models with missing data, applying modern methods to missing, censored, and coarsened data with the goal of Read more...

9780387324487 (acidfree paper) 0387324488 (acidfree paper)


Parameter estimation.
Missing observations (Statistics)

QA276.8 / .T75 2006

519.544 / TSS 2006

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