What Do You Think? Using Expert Opinion to Improve Predictions of Response Propensity Under a Bayesian Framework

Coffey, Stephanie; West, Brady T.; Wagner, James; Elliott, Michael R.

doi:10.12758/mda.2020.05

Cited by 4 publications

(4 citation statements)

References 22 publications

(31 reference statements)

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“…However, these items were amended and retained following the extensive discussion among our experts in the present study. Expert opinion can be used to create the necessary information for prior construction, especially when there is insufficient information in the literature [ 80 ]. In addition, collective data obtained from these items are useful for the development of health education modules on food poisoning among students.…”

Section: Discussionmentioning

confidence: 99%

Validity and Reliability of a Questionnaire on the Knowledge, Attitudes, Perceptions and Practices toward Food Poisoning among Malaysian Secondary School Students: A Pilot Study

et al. 2023

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Children in school settings are at risk of contracting food poisoning due to inadequate food safety practices and safe eating behaviors. This research aimed to develop a valid and reliable questionnaire on the knowledge, attitudes, perceptions, and practices (KAP2) toward food poisoning and its prevention among secondary school students. The questionnaire was developed by considering the Health Belief Model (HBM). A pilot study using a cross-sectional survey was conducted in Tangkak, Johor, among 30 selected students using a convenience sampling method. A pre-test was conducted on 15 secondary school students aged 13–17 years old prior to the pilot study, and they were excluded from the pilot study. The constructed knowledge was assessed using the difficulty and discrimination indices. Meanwhile, the reliability of the attitude, practice, and perception components in the questionnaire were assessed using Cronbach’s alpha. Regarding knowledge (34 items), the difficulty index showed that most items (n = 28) were easy, while one was difficult, and the remaining five were within an acceptable range. In addition, the discrimination index of the knowledge component (34 items) showed that twenty-two, three, and one had good, acceptable, and excellent ranges, respectively. Only eight items had a low discrimination power. All items of the attitude and practice components (10 items for each) showed a corrected item-total correlation value of >0.30. Only four out of twenty-one items of the perception component showed an unacceptable range of <0.30. However, following a discussion with the experts, all items were retained. With the incorporation of the HBM, the 75-item adapted food poisoning KAP2 questionnaire is valid and reliable. It can be utilized to measure and generate food poisoning KAP2 among secondary school students in Malaysia.

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Section: Discussionmentioning

confidence: 99%

Validity and Reliability of a Questionnaire on the Knowledge, Attitudes, Perceptions and Practices toward Food Poisoning among Malaysian Secondary School Students: A Pilot Study

et al. 2023

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“…However, to date, application is scarce in the field of survey monitoring and analysis. Two recent examples are Coffey et al (2020) and West et al (2021). Coffey et al (2020) invited data collection managers as experts and West et al (2021) reported studies in the literature.…”

Section: Introductionmentioning

confidence: 99%

Data Collection Expert Prior Elicitation in Survey Design: Two Case Studies

Schouten

Meijers

et al. 2022

Journal of Official Statistics

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Data collection staff involved in sampling designs, monitoring and analysis of surveys often have a good sense of the response rate that can be expected in a survey, even when this survey is new or done at a relatively low frequency. They make expectations of response rates, and, subsequently, costs on an almost continuous basis. Rarely, however, are these expectations formally structured. Furthermore, the expectations usually are point estimates without any assessment of precision or uncertainty. In recent years, the interest in adaptive survey designs has increased. These designs lean heavily on accurate estimates of response rates and costs. In order to account for inaccurate estimates, a Bayesian analysis of survey design parameters is very sensible. The combination of strong intrinsic knowledge of data collection staff and a Bayesian analysis is a natural next step. In this article, prior elicitation is developed for design parameters with the help of data collection staff. The elicitation is applied to two case studies in which surveys underwent a major redesign and direct historic survey data was unavailable.

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“…et al, (2021). Coffey et al (2020) invited data collection managers as experts and West et al, (2021) reported studies in the literature.…”

Section: Introductionmentioning

confidence: 99%

“…Clearly, translating external data sources to prior beliefs is a requisite for the development of response propensity models. To do so, using a literature review (West et al, 2021) and eliciting expert knowledge (Coffey et al, 2020 andWu et al, 2022) Taken together, this chapter aims to make two contributions in sequential mixed-mode (MM) designs: predicting each survey mode response propensity as accurately as possible and making adaptive decisions in the Bayesian context as optimally as possible. To fulfil this ambition by leveraging historic time-series data in the evaluation, we raise three research questions:…”

Section: Introductionmentioning

confidence: 99%

Improving Predictions of Response Propensities for Effective Adaptive Survey Design (ASD)

Wu¹

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Survey practitioners keep steadily searching for methods to improve effectiveness of adaptive survey design. The adaptation performance depends heavily on precise survey parameter estimates, such as response propensity. Recently, making precise estimates becomes increasingly difficult. The existing methods most often come in conflict with the rare historic data sets for running an infrequent or new survey. Also, methods most often ignore the timeliness of historic data of an ongoing survey. Therefore, this dissertation focuses on developing and applying Bayesian methods in adaptive survey design, both for precise and reliable predictions to make about survey design parameters and for ensuring timeliness of scarce survey resources to allocate. I discuss the Bayesian framework for its ability to include external data through prior distributions and to learn how responses vary in time in order to improve prediction precision. I also discuss effective adaptive survey designs that timely tailor the follow-up strategy to approach nonrespondents in order to enhance the obtained response. The proposed methods in this dissertation are applied to some case studies.

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What Do You Think? Using Expert Opinion to Improve Predictions of Response Propensity Under a Bayesian Framework

Cited by 4 publications

References 22 publications

Validity and Reliability of a Questionnaire on the Knowledge, Attitudes, Perceptions and Practices toward Food Poisoning among Malaysian Secondary School Students: A Pilot Study

Validity and Reliability of a Questionnaire on the Knowledge, Attitudes, Perceptions and Practices toward Food Poisoning among Malaysian Secondary School Students: A Pilot Study

Data Collection Expert Prior Elicitation in Survey Design: Two Case Studies

Improving Predictions of Response Propensities for Effective Adaptive Survey Design (ASD)

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