Statistical Methods to Correct for Proxy Bias in Studies of Older Adults

纠正老年人研究中代理偏差的统计方法

基本信息

批准号：
8437190
负责人：
Michelle Denise Shardell
金额：
$ 13.2万
依托单位：
UNIVERSITY OF MARYLAND BALTIMORE
依托单位国家：
美国
项目类别：
财政年份：
2011
资助国家：
美国
起止时间：
2011-04-01 至 2015-03-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/8437190
关键词：
Accounting Address Aging Behavior Biology Biometry Caregiver Burden Caregivers Caring Clinical Communities Computer software Cross-Sectional Studies Data Development Plans Disease Educational workshop Effectiveness of Interventions Elderly Emotional Epidemiologic Studies Evaluation Exposure to Fracture Future Geriatrics Gerontology Goals Health Hip Fractures Impaired cognition Intervention Interview Lead Link Longitudinal Studies Measurement Measures Mental Depression Mentors Methods Mission Outcome Patient Care Patients Persons Policies Problem Solving Proxy Public Health Quality of life Recovery Recruitment Activity Regression Analysis Relative (related person)Research Research Design Research Personnel Respondent Sampling Selection Bias Shadowing (Histology)Sociology Statistical Methods Structure Testing Validation Visit age related career development cohort computer program design disability improved innovation instrumental activity of daily living investigator training meetings novel strategies outcome forecast programs psychosocial public health relevance response simulation statistics symposium theories tool validation studies

项目摘要

DESCRIPTION (provided by applicant): This proposal has two goals: 1) to develop Dr. Shardell, a biostatistician, into an independent investigator performing research at the interface of biostatistics and gerontology; and 2) to develop statistical methods needed to more appropriately use data from proxy respondents (e.g., relatives or care givers) in epidemiological studies of elderly hip-fracture patients. Regarding the latter goal, a significant problem in epidemiologic studies of hip fracture patients is selection bias due to the large amount of data missing from the most frail and cognitively impaired patients, which may lead to biased results and inaccurate study conclusions. Currently, in order to minimize selection bias due to missing data, proxies are recruited to supply responses in place of patients who are unable or unwilling to respond to interview questions. However, responses from proxies may be systematically biased. This bias is a significant problem because it implies that the standard statistical approach of imputing missing patient data with responses from proxies can lead to inaccurate study conclusions. Therefore, bias from these proxies can impede investigators' ability to accurately identify promising targets of intervention that may improve patients' post-fracture prognosis. To solve this problem, statistical methods originally designed to adjust for selection bias from missing data will be extended to include proxy data. Availability of statistical methods that can correct for proxy bias can help in designing accurately-targeted interventions for postfracture recovery. Computer programs for the methods will be made available online for use by the gerontology community. The new approaches will be validated and compared as part of a future R01 proposal. The three-year mentored research program described in this proposal involves a career development plan that includes coursework in the biology, sociology, and psychosocial aspects of aging; regular meetings with mentors; participation at seminars, workshops, and professional conferences; and exposure to clinical geriatrics settings by shadowing clinician-researchers. Trained investigators with expertise in both biostatistics and gerontology are urgently needed to solve problems in study design, outcome measurement, and statistics that are relevant to aging research.

描述（由申请人提供）：该提案有两个目标：1）将生物统计学家 Shardell 博士培养成为一名独立研究者，在生物统计学和老年学的交叉领域进行研究； 2) 制定统计方法，以便在老年髋部骨折患者的流行病学研究中更恰当地使用代理受访者（例如亲属或护理人员）的数据。关于后一个目标，髋部骨折患者流行病学研究的一个显着问题是选择偏差，因为大多数虚弱和认知障碍患者的数据缺失，这可能导致结果有偏差和研究结论不准确。目前，为了最大限度地减少由于缺失数据而导致的选择偏差，需要招募代理人来代替无法或不愿意回答访谈问题的患者提供答复。然而，代理人的回应可能存在系统性偏见。这种偏差是一个重大问题，因为它意味着将缺失的患者数据与代理的响应进行归集的标准统计方法可能会导致不准确的研究结论。因此，这些指标的偏差可能会妨碍研究人员准确识别有希望的干预目标的能力，从而改善患者的骨折后预后。为了解决这个问题，最初设计用于调整缺失数据的选择偏差的统计方法将扩展到包括代理数据。可以纠正代理偏差的统计方法的可用性有助于设计针对骨折后恢复的准确目标干预措施。这些方法的计算机程序将在线提供，供老年学界使用。新方法将作为未来 R01 提案的一部分进行验证和比较。该提案中描述的为期三年的指导研究计划涉及职业发展计划，其中包括衰老的生物学、社会学和社会心理方面的课程；与导师定期会面；参加研讨会、讲习班和专业会议；并通过跟踪临床医生-研究人员来接触临床老年病学环境。迫切需要训练有素、具有生物统计学和老年学专业知识的研究人员来解决与衰老研究相关的研究设计、结果测量和统计方面的问题。