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The Goldilocks ChallengeRight-Fit Evidence for the Social Sector$
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Mary Kay Gugerty and Dean Karlan

Print publication date: 2018

Print ISBN-13: 9780199366088

Published to Oxford Scholarship Online: May 2018

DOI: 10.1093/oso/9780199366088.001.0001

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Collecting High-Quality Data

Collecting High-Quality Data

(p.118) Chapter 7 Collecting High-Quality Data
The Goldilocks Challenge

Mary Kay Gugerty

Dean Karlan

Oxford University Press

Without high-quality data, even the best-designed monitoring and evaluation systems will collapse. Chapter 7 introduces some the basics of collecting high-quality data and discusses how to address challenges that frequently arise. High-quality data must be clearly defined and have an indicator that validly and reliably measures the intended concept. The chapter then explains how to avoid common biases and measurement errors like anchoring, social desirability bias, the experimenter demand effect, unclear wording, long recall periods, and translation context. It then guides organizations on how to find indicators, test data collection instruments, manage surveys, and train staff appropriately for data collection and entry.

Keywords:   data collection, high-quality data, bias, indicator, validity, reliability, measurement error, surveys, data entry

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