Journal of Economic and Social Measurement - Volume 26, issue 2
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ISSN 0747-9662 (P)
ISSN 1875-8932 (E)
The Journal of Economic and Social Measurement (JESM) is a quarterly journal that is concerned with the investigation of all aspects of production, distribution and use of economic and other societal statistical data, and with the use of computers in that context. JESM publishes articles that consider the statistical methodology of economic and social science measurements. It is concerned with the methods and problems of data distribution, including the design and implementation of data base systems and, more generally, computer software and hardware for distributing and accessing statistical data files. Its focus on computer software also includes the valuation of algorithms and their implementation, assessing the degree to which particular algorithms may yield more or less accurate computed results. It addresses the technical and even legal problems of the collection and use of data, legislation and administrative actions affecting government produced or distributed data files, and similar topics.
The journal serves as a forum for the exchange of information and views between data producers and users. In addition, it considers the various uses to which statistical data may be put, particularly to the degree that these uses illustrate or affect the properties of the data. The data considered in JESM are usually economic or social, as mentioned, but this is not a requirement; the editorial policies of JESM do not place a priori restrictions upon the data that might be considered within individual articles. Furthermore, there are no limitations concerning the source of the data.
Abstract: In panel designs with multiple waves of data collection, the overall survey response rate is a multiplicative function of the wave specific response rates. The 1996 Medical Expenditure Panel Survey (MEPS) Household Component follows this model to acquire data on health care use, expenditures, insurance coverage and sources of payment that cover two consecutive calendar years. An overlapping panel design was implemented, where data covering the second year of a panel are combined with data from…the first year of a new panel. This study identifies the characteristics that distinguish survey participants across waves of the survey from those that only participate in initial rounds and then discontinue their survey participation. The results provide insights regarding the efficacy of the MEPS nonresponse adjustment strategies by comparing the survey estimates from the second year of the longitudinal panel with those from a new panel for the same time period.
Abstract: The evaluation of the level of nonresponse in a survey and the impact of that nonresponse on the survey estimates is an important issue in survey research. It is important to apply the most accurate method of calculating response rates in order to understand the components of nonresponse and to be in a better position to incorporate modifications in the survey procedures as necessary and feasible. Response rates have been defined in a number of ways…for RDD surveys. The standard/traditional method of calculating response rates involves the product of three rates -- the resolution rate, the screening completion rate, and the interview completion rate. The coverage rate (population coverage) has often been reported separately from the response rate. The method presented in this paper has the advantage of combining the coverage rate and the response rate in the calculation of the overall response rate.
Abstract: The 1996 Medical Expenditure Panel Survey - Household Component (MEPS-HC) was designed as a continuous on-going survey to permit annual estimates of health care utilization, expenditures, insurance coverage and sources of payment for the U.S. civilian noninstitutionalized population. Selected as a nationally representative subsample from the National Health Interview Survey, it is characterized by a multi-stage area probability design with an oversample of households with Hispanics and blacks. The 1996 MEPS sample…consists of 195 primary sampling units (PSUs) which contained 10,597 responding NHIS households. In this paper, the precision of survey estimates derived from a 195 PSU design is compared with precision results for alternative sample allocation schemes that preserve the number of sample respondents and the over-sampling of minorities, while varying the number of PSUs and segments. The results provide insights on the impact of alternative sample allocation schemes on the precision of national health care estimates.
Abstract: This paper discusses the methods of probability record linkage and error estimation for the Medical Expenditure Panel Survey (MEPS). MEPS collects medical expenditure data from both household respondents and their medical providers. The medical events reported by the two sources are subject to reporting differences and probability linkage methods are used to determine if pairs of medical events belong to the same entities. Match weights are assigned to pairs of events based on the likelihood of…being a match, and a decision made to declare pairs as matches or nonmatches. The linkage errors include false matches (false positive) when pairs selected are not true matches, and false nonmatches (false negative) when true pairs are omitted. This study used three approaches: manual reviews, cumulative weight curves, and simulation approaches to provide estimates of linkage errors.
Abstract: Despite declines in recent years, inpatient care remains the largest component of national medical expenditures. The U.S. Department of Health and Human Services currently sponsors five data collection efforts that can be used to estimate the utilization of inpatient hospital care in the United States. Through a comparison of 1996 inpatient utilization estimates, this paper describes important methodological considerations when using the different data sources for measuring inpatient use. Our results show that surveys with similar…target populations and methodologies produced similar estimates. In particular, estimates for the household based surveys (NHIS and MEPS-HC) were comparable while those for the hospital discharge surveys (NHDS and HCUP-NIS) were comparable. Hospital discharge surveys produced substantially higher estimates of total discharges than household surveys, which is partly attributable to differences in target populations. Also, data from the MCBS suggest that underreporting may be another explanation for lower estimates from the household surveys.