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At least 181 records · Page 10Linked to original sources
PubMed2006

Unstable inferences? An examination of complex survey sample design adjustments using the Current Population Survey for health services research.

Statistical analysis of the Current Population Survey's Annual Social and Economic Supplement is used widely in health services research. However, the statistical evidence cited from the Current Population Survey (CPS) is not always consistent because researchers use a variety of methods to produce standard errors that are fundamental to significance tests. This analysis examines the 2002 Annual Social and Economic Supplement's (ASEC) estimates of national and state average income, national and state poverty rates, and national and state health insurance coverage rates. Findings show that the standard error estimates derived from the public use CPS data perform poorly compared with the survey design-based estimates derived from restricted internal data, and that the generalized variance parameters currently used by the U.S. Census Bureau in its ASEC reports and funding formula inputs perform erratically. Because the majority of published research (both by academics and Census Bureau analysts) does not make use of the survey design-based information available only on the internal ASEC data file, we argue that the Census Bureau ought to use alternative methods for its official ASEC reports. We also argue that for public use data the Census Bureau should produce a set of replicate weights for the ASEC or release a set of sample design variables that incorporate statistical "noise" to maintain respondent confidentiality (e.g., pseudo-primary sampling units) as other federal government surveys do. This is essential to make appropriate inferences using the ASEC data regarding statistical significance and estimate variance for health policy analysis.

Censuses↗
PubMed1977

[Analysis of the quality of clinical diagnosis from generalized findings of the pathologoanatomic service].

A statistical analysis of generalized data of the pathoanatomical service on quality of clinical diagnosis in curative-prophylactic institutions in 54 administrative territories of the RSFSR was carried out. The structure (extensive indices) and frequency (intensive indices)of erroneous clinical diagnoses referring to the most important classes of diseases were identified. As to the structure of indices and frequency of clinico-anatomic disparities the first place was occupied by oncological diseases (20.1+/-0.11 and 14.2+/-0.22%), the second--by infectious diseases (16.5+/-0.1 and 13.0+/-0.34%), the third--by diseases of the digestive system (14.6+/-0.09 and 13.0+/-0.33%), the forth--by diseases of the urogenital system (14.0+/-0.09 and 12.2+/-0.49%), the fifth--by disease of the respiratory system (12.7+/-0.09 and 10.6+/-0.24%), the sixth--by diseases of the cardiovascular system (11.1+/-0.08 and 8.0+/-0.14%). The recommendation is put forward to carry on annually a complex satistical analysis of extensive and intensive indices of erroneous clinical diagnoses demonstrating the quality of clinical diagnosis in therapeutic institutions of a given administrative territory.

Diagnostic Errors↗
PubMed1997

The SAFE project: community-driven partnerships in health, mental health, and education to prevent early school failure.

This article presents a case study of an innovative school-based health and mental health project that prevents early school failure in one county in Oklahoma. Success is attributed to social work development of broad-based partnerships involving families, schools, communities, and public policy officials. Citizen-driven, these partnerships have meshed previously fixed institutional boundaries in health, mental health, and education to prevent early school failure. The article describes school-family partnerships that form the core of the project's service intervention model. Statistics on service activities and outcomes are presented, along with a discussion of lessons learned for implementation of the project.

Adolescent↗