{"title":"A comparison of methods to approximate standard errors for complex survey data.","authors":"V L Burt, S B Cohen","doi":"","DOIUrl":"","url":null,"abstract":"<p><p>Complex survey designs are characterized by multistage selections with stratification and clustering. The departure from simple random sampling assumptions requires special consideration with regard to variance estimation. Specially designed software packages exist to generate variance estimates for statistics from complex survey data. The variance estimation techniques used include balanced repeated replication, jackknife, and Taylor series linearization. Many complex surveys generate thousands of tables. The computational and publishing costs soar if estimates of standard error are required for all statistics. To decrease these costs, several alternative techniques to approximate the standard errors of estimates are available. These include the widely used relative variance curve, a method based on the average relative standard error, and the average design effect model. In this paper these three methods are compared with respect to accuracy, computational and publishing costs, and ease of implementation.</p>","PeriodicalId":80159,"journal":{"name":"Review of public data use","volume":"12 3","pages":"159-68"},"PeriodicalIF":0.0,"publicationDate":"1984-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"21139065","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}
{"title":"The health planners dilemma and the problem of aggregation bias--an irresolvable conflict.","authors":"Y P Wang, R M Grimes","doi":"","DOIUrl":"","url":null,"abstract":"<p><p>This study examines the potential biases that may exist when data which are collected at one level of aggregation (e.g., the United States) are extrapolated to a smaller area of aggregation (e.g., a census region consisting of several states). Theory would predict that there would be inaccuracies resulting from such extrapolation but does not suggest whether the error would be of sufficient size as to have practical significance for a planner. This study clearly shows that attempting to predict smaller area hospitalizations with large area data is highly inaccurate. It is not only consistent with theory but also shows that the theory has practical value in assessing approaches to estimating hospitalization data.</p>","PeriodicalId":80159,"journal":{"name":"Review of public data use","volume":"12 1","pages":"69-82"},"PeriodicalIF":0.0,"publicationDate":"1984-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"21134095","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}
{"title":"Issues in protecting confidentiality in national health statistics.","authors":"R H Mugge","doi":"","DOIUrl":"","url":null,"abstract":"<p><p>This paper reviews the confidentiality policies of the National Center for Health Statistics (NCHS). It relates these both to the 1974 Privacy Act and to the needs of users of health statistics. The four major issues considered in the paper are: (1) the implications of present confidentiality laws with respect to NCHS, (2) the issue of gaining informed consent in telephone interviews, (3) questions concerning the release of NCHS information on public use data tapes, (4) the implications for NCHS policies of the recently proposed legislation on the confidentiality of federal statistical records.</p>","PeriodicalId":80159,"journal":{"name":"Review of public data use","volume":"12 4","pages":"289-94"},"PeriodicalIF":0.0,"publicationDate":"1984-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"21140806","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}
{"title":"Health care data in the United States.","authors":"D P Rice","doi":"","DOIUrl":"","url":null,"abstract":"<p><p>This article serves as an introduction to the following article, An Inventory of U.S. Health Care Data Bases. As an introduction, this article-reviews the characteristics of U.lS. Health Care Data. These characteristics include a lack of common definition and uniformity of reporting of observations, systems that are sometimes duplicative, and a resistance to data sharing on the part of collecting agencies, arising from the pluralistic American health care economy. Yet federal, state, and local governments as well as private organizations need health data to operate and evaluate their programs. Moreover, recent shifts to block grants and cutbacks in federal funding without accountability requirements will adversely affect our ability to adequately monitor the impact of these programs on the nation's health. The article discusses these data issues, but also emphasizes the need for coordination between the government and private sectors.</p>","PeriodicalId":80159,"journal":{"name":"Review of public data use","volume":"11 2","pages":"79-84"},"PeriodicalIF":0.0,"publicationDate":"1983-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"21130143","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}
{"title":"An inventory of U.S. health care data bases.","authors":"R M Mullner, C S Byre, C L Killingsworth","doi":"","DOIUrl":"","url":null,"abstract":"<p><p>This inventory presents brief descriptions of 144 current (1976-1982) nonbibliographic, computer-readable data bases containing national health care information that have been collected by public and private sector organizations and agencies throughout the United States and that are available to researchers outside the sponsoring organization. The descriptions include information about sponsors, purpose and scope, sampling procedures, frequency, and availability; they also include Medical Subject Headings (MeSH) indicating the content of each data base. In addition, names and telephone numbers of persons to be contacted for further information are provided. The descriptions are indexed by data base titles and by MeSH terms.</p>","PeriodicalId":80159,"journal":{"name":"Review of public data use","volume":"11 2","pages":"85-192"},"PeriodicalIF":0.0,"publicationDate":"1983-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"21130144","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}
{"title":"Toward an inventory of U.S. health care data bases.","authors":"R Mullner, C S Byre","doi":"","DOIUrl":"","url":null,"abstract":"<p><p>Because researchers have lacked convenient and comprehensive sources of information about data available to them from the health care data bases maintained by others in their field, many health care data collection activities are unnecessarily duplicative and many data bases have not been fully exploited. This paper presents the preliminary results of work by the Hospital Data Center of the American Hospital Association on an inventory of current (1976 to the present), nonbibliographic, computer-readable data bases containing national health care information that have been collected by organizations and agencies throughout the United States and that are, or can be, made available to outside researchers. The 30 public and private sector organizations identified as having such data bases are listed, together with the titles and main subject areas of their 112 data bases.</p>","PeriodicalId":80159,"journal":{"name":"Review of public data use","volume":"11 1","pages":"57-65"},"PeriodicalIF":0.0,"publicationDate":"1983-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"21130012","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}
{"title":"Implications of recent mortality trends for the size and composition of the population over 65.","authors":"E M Crimmins","doi":"","DOIUrl":"","url":null,"abstract":"<p><p>Recent mortality declines have been concentrated at the older ages and in the degenerative diseases. In order to examine the implications for the future of continuation of this mortality decline, cause-specific mortality rates by age are projected to the year 2000 assuming that the cause-specific rates of decline experienced during the past decade continue. The projection shows that if such rates of decline persist, by the year 2000 there will be a substantial increase in life expectancy at ages 65 and above and the number of people now over age 65 will be almost 4 million greater than that now officially projected by the U.S. government.</p>","PeriodicalId":80159,"journal":{"name":"Review of public data use","volume":"11 1","pages":"37-48"},"PeriodicalIF":0.0,"publicationDate":"1983-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"21130468","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}
{"title":"Federal statistics: the effect of program cuts on availability, utility and quality.","authors":"K K Wallman","doi":"","DOIUrl":"","url":null,"abstract":"<p><p>Cutbacks in U.S. federal statistical programs have attracted considerable attention during the past year, particularly those that have been associated with efforts to reduce federal government expenditures. However, there have been a variety of changes during the past several years that intentionally or unintentionally have had the effect of reducing federal data resources. Among the legislative actions have been the Paperwork Reduction Act of 1980, which has affected statistical, as well as administrative, data collection. There have also been changes in philosophy concerning the role of the federal government, including both deregulation and the new federalism, that imply a substantial change in federal data collection activities. In addition, the Administration's announced intention to institute user charges will affect the availability of federal statistics. This article reviews some of these changes as seen from the perspective of users of federal statistics who have presented testimony to congressional committees during the past year. It identifies and classifies the principal concerns of these users and provides a guide to the literature.</p>","PeriodicalId":80159,"journal":{"name":"Review of public data use","volume":"10 4","pages":"241-59"},"PeriodicalIF":0.0,"publicationDate":"1982-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"21130361","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}
{"title":"An analysis of alternative imputation strategies for individuals with partial data in the National Medical Care Expenditure Survey.","authors":"S B Cohen","doi":"","DOIUrl":"","url":null,"abstract":"<p><p>Data collection in the National Medical Care Expenditure Survey was applied to the same panel of sample households in six rounds of interviewing, with 1977 as the reference period. Approximately 11 percent of all survey participants provided data for only part of the time they were eligible to respond. To allow for national estimates of relevant health parameters, the data for the partial participants must be adjusted for the entire time frame for which they were eligible. Consequently, three alternative imputation strategies were considered for implementation: a weighted adjustment to the partial data, a substitution of data from complete participants who matched the partial respondents on relevant demographic characteristics, and use of only the data from participants with complete information to characterize the nation. To determine the optimal strategy, a controlled experiment was conducted by artificially creating partial data for participants with complete information, then adjusting the synthetically produced partial data by the three imputation strategies.</p>","PeriodicalId":80159,"journal":{"name":"Review of public data use","volume":"10 3","pages":"153-65"},"PeriodicalIF":0.0,"publicationDate":"1982-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"21180289","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}
{"title":"National social data series: a compendium of brief descriptions.","authors":"R C Taeuber, R C Rockwell","doi":"","DOIUrl":"","url":null,"abstract":"<p><p>This is a compilation of brief descriptions of 101 data bases that together are a large portion of the national body of data as of December 31, 1981, for the study of U.S. social conditions and social change. Most of these data bases were generated by national samples, have substantial social content, and contain observations for more than one time period. The descriptions include information on sponsors, sampling procedures, cycles of data collection, magnetic tapes or other forms of output, and substantive content. Linkages to other data bases are often indicated. Topical and chronological indexes are provided, and key words are supplied for each description. An address and telephone number are provided for persons seeking further information.</p>","PeriodicalId":80159,"journal":{"name":"Review of public data use","volume":"10 1-2","pages":"23-111"},"PeriodicalIF":0.0,"publicationDate":"1982-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"21171413","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}