Quasi-experimental study designs series—paper 9: collecting data from quasi-experimental studies

Ariel M Aloe; Betsy Jane Becker; Maren Duvendack; Jeffrey C Valentine; Ian Shemilt; Hugh Waddington

doi:10.1016/j.jclinepi.2017.02.013

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Quasi-experimental study designs series—paper 9: collecting data from quasi-experimental studies

Journal article

Peer reviewed

Quasi-experimental study designs series—paper 9: collecting data from quasi-experimental studies

Ariel M Aloe, Betsy Jane Becker, Maren Duvendack, Jeffrey C Valentine, Ian Shemilt and Hugh Waddington

Journal of clinical epidemiology, Vol.89, pp.77-83

09/2017

DOI: 10.1016/j.jclinepi.2017.02.013

PMID: 28365305

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https://ueaeprints.uea.ac.uk/id/eprint/63169/1/Accepted_manuscript.pdfView

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Abstract

To identify variables that must be coded when synthesizing primary studies that use quasi-experimental designs. All quasi-experimental (QE) designs. When designing a systematic review of QE studies, potential sources of heterogeneity—both theory-based and methodological—must be identified. We outline key components of inclusion criteria for syntheses of quasi-experimental studies. We provide recommendations for coding content-relevant and methodological variables and outlined the distinction between bivariate effect sizes and partial (i.e., adjusted) effect sizes. Designs used and controls used are viewed as of greatest importance. Potential sources of bias and confounding are also addressed. Careful consideration must be given to inclusion criteria and the coding of theoretical and methodological variables during the design phase of a synthesis of quasi-experimental studies. The success of the meta-regression analysis relies on the data available to the meta-analyst. Omission of critical moderator variables (i.e., effect modifiers) will undermine the conclusions of a meta-analysis.

Quasi-experiment

Effect modifiers

Partial effect size

Moderator variables

Bivariate effect size

Meta-analysis

Details

Title: Subtitle: Quasi-experimental study designs series—paper 9: collecting data from quasi-experimental studies
Creators: Ariel M Aloe - Educational Measurement and Statistics, 368 Lindquist Center, University of Iowa, Iowa City, IA 52242, USA
Betsy Jane Becker - College of Education, Florida State University, 3210D Stone Building, Tallahassee, FL 32306-4453, USA
Maren Duvendack - School of International Development, University of East Anglia, Norwich NR4 7TJ, UK
Jeffrey C Valentine - Department of Counseling and Human Development, University of Louisville, 309 Porter Education Building, Louisville, KY 40292, USA
Ian Shemilt - EPPI-Centre, University College London, 10 Woburn Square, London WC1H 0NR, UK
Hugh Waddington - International Initiative for Impact Evaluation (3ie), 36 Gordon Square, London WC1H 0PD, UK
Resource Type: Journal article
Publication Details: Journal of clinical epidemiology, Vol.89, pp.77-83
DOI: 10.1016/j.jclinepi.2017.02.013
PMID: 28365305
NLM abbreviation: J Clin Epidemiol
ISSN: 0895-4356
eISSN: 1878-5921
Publisher: Elsevier Inc
Language: English
Date published: 09/2017
Academic Unit: Psychological and Quantitative Foundations
Record Identifier: 9983993483502771

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