How high is unemployment? How low is labor force participation? Is obesity more prevalent among men? How large are household expenditures? We study the sources of the relevant official statistics—the Current Population Survey (CPS), the Behavioral Risk Factor Surveillance System (BRFSS), and the Consumer Expenditure Survey (CEX)—and find that the answers depend on whether we look at easy- or at difficult-to-reach respondents, measured by the number of call and visit attempts made by interviewers. A challenge to the (conditionally-)random-nonresponse assumption, these findings empirically substantiate the theoretical warning against making population-wide estimates from surveys with low response rates.
{"title":"Difficulty to Reach Respondents and Nonresponse Bias: Evidence from Large Government Surveys","authors":"Ori Heffetz, Daniel B. Reeves","doi":"10.2139/ssrn.2758787","DOIUrl":"https://doi.org/10.2139/ssrn.2758787","url":null,"abstract":"How high is unemployment? How low is labor force participation? Is obesity more prevalent among men? How large are household expenditures? We study the sources of the relevant official statistics—the Current Population Survey (CPS), the Behavioral Risk Factor Surveillance System (BRFSS), and the Consumer Expenditure Survey (CEX)—and find that the answers depend on whether we look at easy- or at difficult-to-reach respondents, measured by the number of call and visit attempts made by interviewers. A challenge to the (conditionally-)random-nonresponse assumption, these findings empirically substantiate the theoretical warning against making population-wide estimates from surveys with low response rates.","PeriodicalId":356127,"journal":{"name":"HEN: Outcome Measurement (Sub-Topic)","volume":"110 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122567854","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This paper proposes a method of deriving a quality indicator for hospitals using mortality outcome measures. The method aggregates any number of mortality outcome measures observed over several years into a single indicator. We begin with the supposition that there exists an abstract quality index which drives all observed mortality outcomes in each hospital. This abstract quality index is not directly observable but manifested via the observed mortality outcomes, which we make use of to provide an estimate of the abstract quality index. The method is applied to a sample of heart disease episodes extracted from hospital administrative data from the state of Victoria, Australia. Using the quality estimates, we show that teaching hospitals and large regional hospitals provide higher quality of care than other hospitals and this superior performance is related to hospital size.
{"title":"A Two-Stage Estimation of Hospital Quality Using Mortality Outcome Measures: An Application Using Hospital Administrative Data","authors":"Chew Lian Chua, Alfons Palangkaraya, Jongsay Yong","doi":"10.2139/ssrn.1175619","DOIUrl":"https://doi.org/10.2139/ssrn.1175619","url":null,"abstract":"This paper proposes a method of deriving a quality indicator for hospitals using mortality outcome measures. The method aggregates any number of mortality outcome measures observed over several years into a single indicator. We begin with the supposition that there exists an abstract quality index which drives all observed mortality outcomes in each hospital. This abstract quality index is not directly observable but manifested via the observed mortality outcomes, which we make use of to provide an estimate of the abstract quality index. The method is applied to a sample of heart disease episodes extracted from hospital administrative data from the state of Victoria, Australia. Using the quality estimates, we show that teaching hospitals and large regional hospitals provide higher quality of care than other hospitals and this superior performance is related to hospital size.","PeriodicalId":356127,"journal":{"name":"HEN: Outcome Measurement (Sub-Topic)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115876570","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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