Overview of missing data techniques

Ralph B D'Agostino Jr

doi:10.1007/978-1-59745-530-5_17

Overview of missing data techniques

Methods Mol Biol. 2007:404:339-52. doi: 10.1007/978-1-59745-530-5_17.

Author

Ralph B D'Agostino Jr¹

Affiliation

¹ Department of Biostatistical Sciences, Wake Forest University School of Medicine, Winston-Salem, NC, USA.

PMID: 18450058
DOI: 10.1007/978-1-59745-530-5_17

Abstract

Missing data frequently arise in the course of research studies. Understanding the mechanism that led to the missing data is important in order for investigators to be able to perform analyses that will lead to proper inference. This chapter will review different missing data mechanisms, including random and non-random mechanisms. Basic methods will be presented using examples to illustrate approaches to analyzing data in the presence of missing data.

Publication types

Review

MeSH terms

Animals
Cell Proliferation / drug effects
Data Interpretation, Statistical*
Enzymes / metabolism
Male
Mice
Models, Statistical*
Prostatic Neoplasms / therapy
Proteins / metabolism

Substances

Enzymes
Proteins