Jump to ContentJump to Main Navigation
Handbook of Meta-analysis in Ecology and Evolution$
Users without a subscription are not able to see the full content.

Julia Koricheva, Jessica Gurevitch, and Kerrie Mengersen

Print publication date: 2013

Print ISBN-13: 9780691137285

Published to Princeton Scholarship Online: October 2017

DOI: 10.23943/princeton/9780691137285.001.0001

Show Summary Details
Page of

PRINTED FROM PRINCETON SCHOLARSHIP ONLINE (www.princeton.universitypressscholarship.com). (c) Copyright Princeton University Press, 2022. All Rights Reserved. An individual user may print out a PDF of a single chapter of a monograph in PRSO for personal use.date: 18 May 2022

Extraction and Critical Appraisal of Data

Extraction and Critical Appraisal of Data

(p.52) 5 Extraction and Critical Appraisal of Data
Handbook of Meta-analysis in Ecology and Evolution

Peter S. Curtis

Kerrie Mengersen

Marc J. Lajeunesse

Hannah R. Rothstein

Gavin B. Stewart

Princeton University Press

This chapter discusses the data extraction process, meta-analysis database, and critical appraisal of data. The efficient and accurate extraction of data from primary studies is an important component of successful research reviews. It is one of the most time-consuming parts of a research review and should be approached with the goal of repeatability and transparency of results. Careful definition of the research question and identification of the effect size metric(s) to be used are prerequisites to efficient data extraction. The extraction spreadsheet may simply be appended to a growing database stored in a single spreadsheet (also known as “flat file database”) (e.g., Microsoft Excel, Lotus, Quattro Pro), but it may be advantageous to develop relational databases (e.g., by using Microsoft Access, Paradox or dBase software), particularly for large or complex data. During the process of data extraction the investigator also has an opportunity for critical appraisal of data quality. One approach to quantitative assessment of study quality has been the use of numerical scales in which points are assigned to specific elements of the study and summed to produce an overall quality score.

Keywords:   data extraction, data appraisal, meta-analysis database, study quality, data quality

Princeton Scholarship Online requires a subscription or purchase to access the full text of books within the service. Public users can however freely search the site and view the abstracts and keywords for each book and chapter.

Please, subscribe or login to access full text content.

If you think you should have access to this title, please contact your librarian.

To troubleshoot, please check our FAQs , and if you can't find the answer there, please contact us.