Data from: A Bayesian hierarchical approach to quantifying stakeholder attitudes toward conservation in the presence of reporting error

Stakeholder support is vital for achieving conservation success, yet there
are few reliable mechanisms to monitor stakeholder attitudes towards
conservation. Importantly, few approaches account for bias arising from
reporting errors; that is, reporting a positive attitude towards
conservation when the respondent actually does not have one (a false
positive error), or not reporting a positive attitude when the respondent
is positive towards conservation (a false negative error). We borrow from
developments in applied conservation science to use a Bayesian
hierarchical model to quantify stakeholder attitudes as the probability of
having a positive attitude towards wildlife, notionally (or in abstract
terms) and at localized scales. The model allows us to assess stakeholder
attitudes, and factors influencing these attitudes, while accounting for
false negative and false positive reporting errors. We show through
simulations that this method has lower bias than naïve estimates of the
proportion of respondents who are positive towards wildlife, or
Likert‐scores. We demonstrate the utility of the model by applying it to
questionnaire surveys on Asian elephants Elephas maximus in the
Kaziranga–Karbi Anglong landscape, Northeast India. After accounting for
reporting errors, we estimated the probability of being positive towards
elephants notionally as 0.85; at a localized scale, however, the
proportion of respondents that were positive towards elephants was 50%. In
comparison, without accounting for reporting errors, the proportion of
respondents professing positive attitudes towards elephants in at least
one of the certain questions, was 0.69 and 0.23, notionally and at local
scales, respectively. False (positive and negative) reporting
probabilities were consistently non‐zero (0.22–0.68). We submit that
regular and reliable assessment of stakeholder attitudes––combined with an
understanding of factors contributing to variation in attitudes––can feed
into participatory conservation monitoring programs, help assess the
success of initiatives aimed at facilitating human behavioral change, and
inform conservation decision‐making.