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Design and Analysis of Time-Series Experiments

List Price: $61.00
SKU:
9781593119805
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  • Product Details

    Author:
    Gene V. Glass, Victor L. Willson, John M. Gottman, Gene V. Glass
    Format:
    Paperback
    Pages:
    264
    Publisher:
    Emerald Publishing Limited (August 14, 2008)
    Imprint:
    Information Age Publishing
    Language:
    English
    Audience:
    Professional and scholarly
    ISBN-13:
    9781593119805
    ISBN-10:
    1593119801
    Weight:
    13.12oz
    Dimensions:
    6.14" x 9.21" x 0.55"
    File:
    TWO RIVERS-PERSEUS-Metadata_Only_Perseus_Distribution_Customer_Group_Metadata_20251107163220-20251107.xml
    Folder:
    TWO RIVERS
    List Price:
    $61.00
    Country of Origin:
    United Kingdom
    Pub Discount:
    35
    Case Pack:
    1
    As low as:
    $57.95
    Publisher Identifier:
    P-PER
    Discount Code:
    H
  • Overview

    Hailed as a landmark in the development of experimental methods when it appeared in 1975, Design and Analysis of Time-Series Experiments is available again after several years of being out of print.

    Gene V Glass, Victor L. Willson and John M. Gottman have carried forward the design and analysis of perhaps the most powerful and useful quasi-experimental design identified by their mentors in the classic Campbell & Stanley text Experimental and Quasi-experimental Design for Research (1966). In an era when governments seek to resolve questions of experimental validity by fiat and the label 'Scientifically Based Research' is appropriated for only certain privileged experimental designs, nothing could be more appropriate than to bring back the classic text that challenges doctrinaire opinions of proper causal analysis.

    Glass, Willson & Gottman introduce and illustrate an armamentarium of interrupted time-series experimental designs that offer some of the most powerful tools for discovering and validating causal relationships in social and education policy analysis. Drawing on the ground-breaking statistical analytic tools of Box & Jenkins, the authors extend the comprehensive autoregressive-integrated-moving-averages (ARIMA) model to accommodate significance testing and estimation of the effects of interventions into real world time-series. Designs and full statistical analyses are richly illustrated with actual examples from education, behavioral psychology, and sociology.