Show simple item record

dc.contributor.authorSchmidt, Jennifer
dc.contributor.authorBeaman, Jay
dc.contributor.authorVaske, Jerry
dc.contributor.authorHuan, Tzung-Cheng
dc.date.accessioned2018-08-08T22:37:14Z
dc.date.available2018-08-08T22:37:14Z
dc.date.issued2015-04-01
dc.identifier.urihttp://hdl.handle.net/11122/9567
dc.description.abstractImprecision in respondent recall can cause response heaping in frequency data for particular values (e.g., 5, 10, 15). In human dimensions research, heaping can occur for variables such as days of participation (e.g., hunting, fishing), animals/fish harvested, or money spent on licenses. Distributions with heaps can bias population estimates because the means and totals can be inflated or deflated. Because bias can result in poor management decisions, determining if the bias is large enough to matter is important. This note introduces the logic and flow of a deheaping program that estimates bias in means and totals when people use approximate responses (i.e., prototypes). The program can make estimates even when spikes occur due to bag limits. The program is available online, and smooths heaps at multiples of 5 (numbers ending in 5 and 0) and 7 (e.g., 7, 14, 21), and produces standard deviations in estimates.en_US
dc.language.isoen_USen_US
dc.publisherTaylor and Francisen_US
dc.subjectresponse heapingen_US
dc.subjectdeheapingen_US
dc.subjectprototype useen_US
dc.subjectestimate biasen_US
dc.titleMeasuring and Correcting Response Heaping Arising From the Use of Prototypesen_US
dc.typeBook chapteren_US
refterms.dateFOA2020-03-06T02:01:55Z


Files in this item

Thumbnail
Name:
2015_04-MeasuringandCorrecting ...
Size:
203.2Kb
Format:
PDF

This item appears in the following Collection(s)

Show simple item record