The Use of Multiples in Anglers' Recall of Participation and Harvest Estimates: Some Results and Implications

Vaske, Jerry J.; Huan, Tzung‐Cheng; Beaman, Jay

doi:10.1080/714044498

Cited by 17 publications

(17 citation statements)

References 14 publications

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“…For example, respondents may use estimation heuristics where frequency of participation (or harvest) is estimated by recalling sample episodes (Tversky and Kahneman 1974). More salient episodes (e.g., successful hunts) are more likely to be recalled, resulting in over estimation (Vaske et al 2003). When events are numerous, similar, and occur regularly, respondents may use rule-based cognitive processes (Burton and Blair 1991).…”

Section: Cognitive Processes In Harvest Survey Responsesmentioning

confidence: 99%

“…For example, if an individual is asked how many ringnecked pheasants (Phasianus colchicus) he or she harvested during the last 3 months, the response might be 24, if the person recalls hunting about once a week for 3 months and remembers harvesting approximately 2 birds per hunt (i.e., once a week * 4 weeks per month * 3 months * 2 birds per day = 24). Formula-based response styles may result in bias because the multipliers used are approximations that can be systematically in error (Vaske et al 2003).…”

Section: Cognitive Processes In Harvest Survey Responsesmentioning

confidence: 99%

“…These processes potentially yield responses that differ from what actually happened. Approximate responses are suggested by response heaps (e.g., spikes in the data for numbers ending in zero or 5) that occur because some responses are given more often than would be expected by chance (Sen 1973;Tarrant and Manfredo 1993;Anderson et al 1996;Vaske et al 1996Vaske et al , 2003Beaman et al 1998).…”

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confidence: 99%

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Cognitive Processes in Hunters' Recall of Participation and Harvest Estimates

Beaman¹,

Vaske

Miller

2005

Journal of Wildlife Management

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We hypothesized that hunters' use of approximate responses for participation and harvest survey questions was prompted by the cognitive complexity of giving an exact answer. Approximate responses we considered were: (1) rounding days of participation and harvest to numbers ending in zero or 5 (0–5 prototypes) and (2) multiplying days of participation by an integer to approximate harvest. Both types of survey responses result in response heaps (spikes in the data) that can introduce bias. Our analyses were based on the frequency of responses in heaps relative to all responses in a neighborhood (a set of responses close to each other). Data from the Illinois hunter harvest survey (1998–2000) showed that the relative frequency of using approximate responses in a neighborhood was statistically constant across years and species despite differences in day‐harvest frequencies. Our results supported accepting the hypothesis that survey responses are influenced by the cognitive complexity of formulating a response. We discuss the following strategies for identifying, reducing, and correcting bias in estimates derived from surveys: (1) basic research to identify the extent to which respondents use prototypes when answering participation and harvest questions; (2) survey methodology modifications to increase the accuracy of answers; and (3) the development of bias correction factors.

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Section: Cognitive Processes In Harvest Survey Responsesmentioning

confidence: 99%

Section: Cognitive Processes In Harvest Survey Responsesmentioning

confidence: 99%

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confidence: 99%

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Cognitive Processes in Hunters' Recall of Participation and Harvest Estimates

Beaman¹,

Vaske

Miller

2005

Journal of Wildlife Management

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“…; Connelly & Brown ; Vaske et al . ), although Connelly and Brown () found the opposite trend. This illustrates that the underlying mechanism behind this bias is more complex than previously thought, which might reflect diversity in angler behaviour (Arlinghaus et al .…”

Section: Discussionmentioning

confidence: 92%

Estimating recreational harvest using interview‐based recall survey: implication of recalling in weight or numbers

Sparrevohn

2012

Fisheries Management Eco

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For many overfished marine stocks, recreational fishing continues even though recovery plans are implemented and commercial landings regulated. In such cases, unbiased and precise estimates of recreational harvest are important for successful management. Harvest estimation often relies on interviewed‐based surveys where fishers are asked to recall harvest within a given timeframe. However, the importance of whether fishers are requested to provide figures in weight or number is unresolved. Therefore, a recall survey aiming at estimating recreational harvest was designed, such that respondents could report harvest using either weight or numbers. It was found that: (1) a preference for reporting in numbers dominated; (2) reported mean individual weight of fish caught, differed between units preferences; and (3) when an estimate of total harvest in weight are calculated, these difference could result in a substantial bias through the conversion from numbers to weight. Based upon these results it is recommended that recreational harvest should be requested in numbers and not weight.

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“…As the frequency of participation in a behavior and/or quantity to be estimated increases, episodic enumeration can yield to estimation heuristics where frequency is estimated by recalling sample episodes (Tversky & Kahneman, 1974). More salient episodes tend to be recalled more frequently, resulting in overestimation (Vaske, Huan, & Beaman, 2003). When events are numerous, similar, and occur regularly, respondents may use formula-based multipliers (Burton & Blair, 1991).…”

Section: Past Researchmentioning

confidence: 99%

Measuring and Correcting Response Heaping Arising From the Use of Prototypes

Beaman

Vaske

Schmidt

et al. 2015

Human Dimensions of Wildlife

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Imprecision 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.

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The Use of Multiples in Anglers' Recall of Participation and Harvest Estimates: Some Results and Implications

Cited by 17 publications

References 14 publications

Cognitive Processes in Hunters' Recall of Participation and Harvest Estimates

Cognitive Processes in Hunters' Recall of Participation and Harvest Estimates

Estimating recreational harvest using interview‐based recall survey: implication of recalling in weight or numbers

Measuring and Correcting Response Heaping Arising From the Use of Prototypes

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