Jump to ContentJump to Main Navigation

You are looking at 1-4 of 4 items

  • Keywords: multiple imputation x
Clear All Modify Search

View:

Strategies to Approximate Random Sampling and Assignment

Patrick Dattalo

Published in print:
2009
Published Online:
February 2010
ISBN:
9780195378351
eISBN:
9780199864645
Item type:
book
Publisher:
Oxford University Press
DOI:
10.1093/acprof:oso/9780195378351.001.0001
Subject:
Social Work, Research and Evaluation

Random sampling (RS) and random assignment (RA) are considered by many researchers to be the definitive methodological procedures for maximizing external and internal validity. However, there is a ... More


Methods for handling missing data

Paul Clarke and Rebecca Hardy

in Epidemiological Methods in Life Course Research

Published in print:
2007
Published Online:
September 2009
ISBN:
9780198528487
eISBN:
9780191723940
Item type:
chapter
Publisher:
Oxford University Press
DOI:
10.1093/acprof:oso/9780198528487.003.0007
Subject:
Public Health and Epidemiology, Public Health, Epidemiology

This chapter begins by describing helpful typologies of missing data based on pattern and non-response mechanisms. It then summarizes a collection of commonly used but imperfect methods for dealing ... More


Statistical Alternatives and Supplements to Random Sampling

Patrick Dattalo

in Strategies to Approximate Random Sampling and Assignment

Published in print:
2009
Published Online:
February 2010
ISBN:
9780195378351
eISBN:
9780199864645
Item type:
chapter
Publisher:
Oxford University Press
DOI:
10.1093/acprof:oso/9780195378351.003.0003
Subject:
Social Work, Research and Evaluation

This chapter describes the following alternatives and complements to RS in terms of their assumptions, implementations, strengths, and weaknesses: (1) randomization tests; (2) multiple imputation; ... More


Missing data: mechanisms, methods, and messages

Shinichi Nakagawa

in Ecological Statistics: Contemporary theory and application

Published in print:
2015
Published Online:
April 2015
ISBN:
9780199672547
eISBN:
9780191796487
Item type:
chapter
Publisher:
Oxford University Press
DOI:
10.1093/acprof:oso/9780199672547.003.0005
Subject:
Biology, Biomathematics / Statistics and Data Analysis / Complexity Studies, Ecology

Missing data are ubiquitous in ecological and evolutionary data sets as in any other branch of science. The common methods used to deal with missing data are to delete cases containing missing data, ... More


View: