Effective Observational Strategies for Health Survey Interviewers
Effective Observational Strategies for Health Survey Interviewers
批准号:
8739300
负责人:
Brady T West
金额:
$7.56万
依托单位国家:
美国
项目类别:
财政年份:
2013
资助国家:
美国
项目状态:
已结题
起止时间:
2013-09-21 至 2016-08-31
关键词:
AnthropologyAreaCensusesCluster AnalysisCollectionDataData CollectionEarEffectivenessEyeFamilyGrowthHealthHealth SurveysHouseholdHumanInterviewerLeadLiteratureMeasuresMethodsMichiganNational Health Interview SurveyNonrespondentPoliciesPopulationPsychologyPublic HealthResearchResearch MethodologyResearch Project GrantsRespondentSamplingSourceSubgroupSurveysTechniquesTrainingUniversitiesWorkbasecost effectivedesignimprovedmultilevel analysisprogramspsychologicpublic health relevanceresponsetheories
中文摘要
描述(申请人提供):在大型健康调查中,如全国健康访谈调查,(NHIS,目前由美国人口普查局进行)和全国家庭增长调查(NSFG,目前由密歇根大学进行),调查人员记录的描述所有抽样单位的选定特征的观察结果代表了一个有希望的,具有成本效益的辅助信息来源,调查统计人员可用于调查估计数的无答复调整和响应调查设计。访谈者是调查机构在实地的眼睛和耳朵,一个小的文献表明,访谈者可以成功地记录与关键调查措施和反应倾向相关的抽样单位的特征的观察结果。不幸的是,这些观察结果已经被证明是容易出错的,越来越多的研究表明,增加的误差水平的观察可以限制无反应调整的有效性。此外,在这方面的初步工作发现,即使在控制了访谈者和家庭水平的协变量后,访谈者的观察结果的准确性也有很大差异。没有现有的研究试图确定这种差异的其他来源。 基于心理学和人类学文献中对人类观察中的偏差来源的研究,以及初步研究表明调查人员在观察策略方面存在差异,拟议的研究旨在:1)对NSFG调查人员提供的数千个理由进行定性分析,这些理由是他们对所有抽样NSFG家庭的两个关键特征进行观察的理由; 2)使用聚类分析技术,以确定是否存在独特的NSFG采访者亚组的基础上观察策略明显的理由;以及3)使用多水平建模技术来比较所识别的访问者分组中的两个观察结果的准确性,控制观测精度的其他相关因素。成功完成拟议的研究将为健康调查的设计者提供有效的观察策略的证据,这些策略可以帮助标准化采访者观察的收集,并展示调查机构可以用来为采访者培训提供信息的新研究方法。
英文摘要
DESCRIPTION (provided by applicant): In large health surveys like the National Health Interview Survey (NHIS, currently conducted by the U.S. Census Bureau) and the National Survey of Family Growth (NSFG, currently conducted by the University of Michigan), observations that interviewers record describing selected features of all sampled units represent a promising, cost-effective source of auxiliary information that survey statisticians can use for nonresponse adjustment of survey estimates and responsive survey designs. Interviewers are the eyes and ears of the survey organization out in the field, and a small literature has shown that interviewers can successfully record observations on features of sampled units that are correlated with both key survey measures and response propensity. Unfortunately, these observations have been shown to be prone to error, and a growing body of research has demonstrated that increasing levels of error in the observations can limit the effectiveness of nonresponse adjustments. Furthermore, initial work in this area has found that interviewers vary substantially in the accuracy of their observations, even after controlling for interviewer- and household-level covariates. No existing study has attempted to identify additional sources of this variance. Motivated by literature in psychology and anthropology that examines sources of bias in human observation and preliminary work suggesting that interviewers vary in terms of their observational strategies, the proposed research aims to: 1) perform a qualitative analysis of several thousand justifications provided by NSFG interviewers for their observations on two key features of all sampled NSFG households; 2) use cluster analysis techniques to determine whether unique subgroups of NSFG interviewers exist based on the observational strategies evident in their justifications; and 3) use multilevel modeling techniques to compare the accuracy of the two observations among the identified subgroups of interviewers, controlling for other relevant correlates of observation accuracy. Successful completion of the proposed research will provide designers of health surveys with evidence of effective observational strategies that can help to standardize the collection of interviewer observations, and demonstrate a new research methodology that survey agencies can use to inform interviewer training.
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会议论文
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