Difference between revisions of "Recall Bias"
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< | <onlyinclude>Recall bias is bias caused by inaccurate or incomplete recollection of events by the respondent. It is a particular concern for retrospective survey questions. </onlyinclude> | ||
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== Read First == | |||
* Research shows that lower salience and longer recall periods increase forgetfulness [http://blogs.worldbank.org/impactevaluations/decomposing-response-error-improve-consumption-survey-design] [http://www.sciencedirect.com/science/article/pii/S0304387811000939] | |||
== Guidelines == | |||
=== How long is "too long" for recall? === | |||
It depends on the type of event respondents are being asked to recall. Research shows strong evidence of recall bias in food consumption, but little evidence for agricultural production. | |||
As a rule of thumb, infrequent events (e.g. purchases of major assets) will be memorable for longer periods of time than routine events (e.g. use of public transportation). | |||
== | ===How to avoid recall bias?=== | ||
Useful strategies: | |||
# Reduce recall periods as much as possible. For example, add follow-up surveys by phone, or personal diaries. | |||
# Conduct focus groups to understand salience of the indicator in question, and gauge a reasonable recall period. | |||
# When [[Survey Pilot|Piloting your Survey]], carefully test recall periods; if possible try shorter and longer periods and check for differences in variance | |||
== Back to Parent == | == Back to Parent == | ||
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== Additional Resources == | == Additional Resources == | ||
* | * DIME Analytics (World Bank), [https://osf.io/rqb5m/ Survey Instrument Design and Pilot] | ||
* IFPRI, [https://www.ifpri.org/blog/do-you-remember-measuring-anchoring-bias-recall-data Measuring anchoring bias in recall data] | |||
* Jed Friedman (World Bank), [http://blogs.worldbank.org/impactevaluations/decomposing-response-error-improve-consumption-survey-design Response Error in Consumption Surveys], and the [https://documents1.worldbank.org/curated/en/122481467999693721/pdf/WPS7646.pdf related paper] | |||
* Financial Access Initiative, [http://www.financialaccess.org/blog/2015/7/30/reliability-of-self-reported-data-recall-bias The Reliability of Self-reported Data] | |||
* Jishnu Das, Jeffrey Hammer, Carolina Sánchez-Paramo, [http://www.sciencedirect.com/science/article/pii/S0304387811000708 The impact of recall periods on reported morbidity and health seeking behavior] | |||
* Kathleen Beegle, Calogero Carletto, Kristen Himelein, [http://www.sciencedirect.com/science/article/pii/S0304387811000939 Reliability of recall in agricultural data] | |||
* Philip Wollburg, Marco Tiberti and Alberto Zezza, [https://www.sciencedirect.com/science/article/pii/S0306919220302098?fbclid=IwAR1at8ueH2h4j3mHXlGvcIGEX4wgoxTgN6IdmxGejJJsz3DJkmra2bn6jas Recall length and measurement error in agricultural surveys] | |||
[[Category: Questionnaire Design]] | [[Category: Questionnaire Design]] | ||
Latest revision as of 18:56, 19 October 2021
Recall bias is bias caused by inaccurate or incomplete recollection of events by the respondent. It is a particular concern for retrospective survey questions.
Read First
Guidelines
How long is "too long" for recall?
It depends on the type of event respondents are being asked to recall. Research shows strong evidence of recall bias in food consumption, but little evidence for agricultural production. As a rule of thumb, infrequent events (e.g. purchases of major assets) will be memorable for longer periods of time than routine events (e.g. use of public transportation).
How to avoid recall bias?
Useful strategies:
- Reduce recall periods as much as possible. For example, add follow-up surveys by phone, or personal diaries.
- Conduct focus groups to understand salience of the indicator in question, and gauge a reasonable recall period.
- When Piloting your Survey, carefully test recall periods; if possible try shorter and longer periods and check for differences in variance
Back to Parent
This article is part of the topic Questionnaire Design
Additional Resources
- DIME Analytics (World Bank), Survey Instrument Design and Pilot
- IFPRI, Measuring anchoring bias in recall data
- Jed Friedman (World Bank), Response Error in Consumption Surveys, and the related paper
- Financial Access Initiative, The Reliability of Self-reported Data
- Jishnu Das, Jeffrey Hammer, Carolina Sánchez-Paramo, The impact of recall periods on reported morbidity and health seeking behavior
- Kathleen Beegle, Calogero Carletto, Kristen Himelein, Reliability of recall in agricultural data
- Philip Wollburg, Marco Tiberti and Alberto Zezza, Recall length and measurement error in agricultural surveys