Strategies to Approximate Random Sampling and Assignment (Pocket Guide to Social Work Research Methods)

Strategies to Approximate Random Sampling and Assignment (Pocket Guide to Social Work Research Methods)

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Strategies to Approximate Random Sampling and Assignment (Pocket Guide to Social Work Research Methods)

Random sampling and random assignment are considered by many researchers to be the definitive methodological procedures for maximizing external and internal validity. However, there is a daunting list of legal, ethical, and practical barriers to implementing random sampling and random assignment. While there are no easy ways to overcome these barriers, social workers should seek and utilize strategies that minimize sampling and assignment bias. These methodological and statistical strategies form the book's core.

In step-by-step chapters liberally illustrated with examples using a variety of software packages, Dattalo guides readers in selecting and implementing an appropriate strategy. Readers will gain confidence in using such techniques as exemplar sampling, sequential sampling, randomization tests, multiple imputation, mean-score logistic regression, partial randomization, constructed comparison groups, instrumental variables methods, and propensity scores. Each approach will be cataloged in such a way as to highlight its underlying assumptions, implementation strategies, and strengths and weaknesses.

Screen shots, annotated resources, and a companion website make this a valuable tool for students, teachers, and researchers seeking a single source that provides a diverse set of tools that will maximize a study's validity when random sampling and random assignment are neither possible nor practical.

Technical Specifications

Country
USA
Author
Patrick Dattalo
Binding
Kindle Edition
Edition
1
EISBN
9780199702930
Format
Kindle eBook
Label
Oxford University Press
Manufacturer
Oxford University Press
NumberOfPages
216
PublicationDate
2009-10-29
Publisher
Oxford University Press
ReleaseDate
2009-10-29
Studio
Oxford University Press