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Information on the cost of fishing is integral in measuring fisheries performance and correctly evaluating the economic impacts of fisheries regulations and management rules. However, limited availability of cost data often renders such analyses either incomplete or implausible. This study discusses a survey effort that was undertaken in the Northeast US to collect fisheries annual fixed cost data directly from commercial fishermen. Stratified random samples of fishing vessel owners were surveyed in 2012 and 2013. An overview of the survey procedures, sample selection and administration is given here. The data cleaning process, non-response bias and data summaries are also presented. A modeling framework is discussed for estimating fisheries cost data. Robust cost models in combination with regular data collection efforts will allow for more complete economic and financial analyses relevant to fisheries management and conservation. [ABSTRACT FROM AUTHOR]

Many health surveys conduct an initial household interview to obtain demographic information and then request permission to obtain detailed information on health outcomes from the respondent's health care providers. A ‘complete response’ results when both the demographic information and the detailed health outcome data are obtained. A ‘partial response’ results when the initial interview is complete but, for one reason or another, the detailed health outcome information is not obtained. If ‘complete responders’ differ from ‘partial responders’ and the proportion of partial responders in the sample is at least moderately large, statistics that use only data from complete responders may be severely biased. We refer to bias that is attributable to these differences as ‘partial non-response’ bias. In health surveys it is customary to adjust survey estimates to account for potential differences by employing adjustment cells and weighting to reduce bias from partial response. Before making these adjustments, it is important to ask whether an adjustment is expected to increase or decrease bias from partial non-response. After making these adjustments, an equally important question is ‘How well does the method of adjustment work to reduce partial non-response bias?’. The paper describes methods for answering these questions. Data from the US National Immunization Survey are used to illustrate the methods. [ABSTRACT FROM AUTHOR]

Background: Non-random non-response bias in surveys requires time-consuming, complicated, post-survey analyses. Our goal was to see if modifying cover letter information would prevent non-random non-response bias altogether. Our secondary goal tested whether larger incentives would reduce non-response bias., Methods: A mailed, survey of 480 male and 480 female, nationally representative, Operations Enduring Freedom, Iraqi Freedom, or New Dawn (OEF/OIF/OND) Veterans applying for Department of Veterans Affairs (VA) disability benefits for posttraumatic stress disorder (PTSD). Cover letters conveyed different information about the survey's topics (combat, unwanted sexual attention, or lifetime and military experiences), how Veterans' names had been selected (list of OEF/OIF/OND Veterans or list of Veterans applying for disability benefits), and what incentive Veterans would receive ($20 or $40). The main outcome, non-response bias, measured differences between survey respondents' and sampling frame's characteristics on 8 administrative variables, including Veterans' receipt of VA disability benefits and exposure to combat or military sexual trauma. Analysis was intention to treat. We used ANOVA for factorial block-design, logistic, mixed-models to assess bias and multiple imputation and expectation-maximization algorithms to assess potential missing mechanisms (missing completely at random, missing at random, or not random) of two self-reported variables: combat and military sexual assault., Results: Regardless of intervention, men with any VA disability benefits, women with PTSD disability benefits, and women with combat exposure were over-represented among respondents. Interventions explained 0.0 to 31.2% of men's variance and 0.6 to 30.5% of women's variance in combat non-response bias and 10.2 to 43.0% of men's variance and 0.4 to 31.9% of women's variance in military sexual trauma non-response bias. Non-random assumptions showed that men's self-reported combat exposure was overestimated by 19.0 to 28.8 percentage points and their self-reported military sexual assault exposure was underestimated by 14.2 to 28.4 percentage points compared to random missingness assumptions. Women's self-reported combat exposure was overestimated by 8.6 to 10.6 percentage points and military sexual assault exposure, by 1.2 to 6.9 percentage points., Conclusions: Our interventions reduced bias in some characteristics, leaving others unaffected or exacerbated. Regardless of topic, researchers are urged to present estimates that include all three assumptions of missingness., (© 2022. The Author(s).)

Background: Patient satisfaction surveys are increasingly utilized to measure the patient experience and as a tool to assess the quality of care delivered by medical providers. Press Ganey (PG) is the largest provider of tools for patient satisfaction measurement and analysis. The purpose of this study was to determine if patient satisfaction surveys were subject to selection and/ or nonresponse bias., Methods: Patients seen in an outpatient academic orthopedic clinic were included in this retrospective cohort study. Demographic data included age, race, gender, marital status, primary payer, and native language. All surveys were administered by PG Associates per internal protocols adhering to exclusion criteria within the institutional contract with PG Associates., Results: 3.5% of outpatient encounters generated PG survey data, which were generated by 9.1% of all patients evaluated. The population of patients who were administered as well as patients who responded to the patient satisfaction survey represented a unique population with regards to age, race, gender, marital status, insurance status, and native language., Conclusions: Demographically, patients who were administered and patients who responded to PG surveys differed from the overall population of patients seen in an outpatient orthopedic setting, evidencing both selection and non-response bias. Because of these differences, and considering the small number of survey returned, caution should be exercised when interpreting and applying these data. Level of Evidence: III., Competing Interests: Disclosures: The authors report no potential conflicts of interest related to this study.

Comprehensive land use planning at the county level has been a focus of a good deal of public attention in the U.S. in the post-World War II era. Because Extension is typically very active at the county level and provides substantial expertise on land use at the university level, it has long played a significant role in the planning process. This article reports the findings of a survey among residents of an exurban community on land use designed to obtain public opinion prior to the update of a comprehensive plan, contributing a sense of public inclusion to the process. [ABSTRACT FROM AUTHOR]