PubMed Health⌕ Search

PubMed · 7119920

Computerized approach to verifying study population data in occupational epidemiology.

Abstract

IN a previous paper a method was presented for verifying the completeness of occupational study populations independently of company-held records. The basis for the verification scheme was the Employers Quarterly Report on Earnings (Internal Revenue Service Form 941) that is submitted to the IRS each quarter of every year for all employees on a company payroll. In employing the verification scheme two approaches can be taken in determining how many and which quarterly reports are selected: (1) If the work force is large and/or many years are surveyed, a probability sample of years and quarters within years can be selected, allowing inferences to be made with respect to the entire study population. (2) If the number of survey years and/or the size of the work force is sufficiently small, copies of all quarterly returns for each survey year can be requested thus allowing a comprehensive check for completeness to be conducted. Te verification method described in the previous paper concentrated primarily on the first-mentioned approach. The second approach is herein being dealt with as well as a computerized method for verifying the completeness of study populations. In addition a new computerized method is described that utilizes the quarterly reports as an unbiased data base for checking the accuracy of certain work history data as developed from company records. An application of the computerized methods is given using data from a recent historical-prospective study of chemical production workers.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

G M Marsh. 1982. Computerized approach to verifying study population data in occupational epidemiology.. https://doi.org/10.1097/00043764-198208000-00014

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related citations

Evaluation of sites for the location of WEEE recycling plants in Spain.

As a consequence of new European legal regulations for treatment of waste electrical and electronic equipment (WEEE), recycling plants have to be installed in Spain. In this context, this contribution describes a method for ranking of Spanish municipalities according to their appropriateness for the installation of these plants. In order to rank the alternatives, the discrete multi-criteria decision method PROMETHEE (Preference Ranking Organisation METHod for Enrichment Evaluations), combined with a surveys of experts, is applied. As existing plants are located in North and East Spain, a significant concentration of top ranking municipalities can be observed in South and Central Spain. The method does not present an optimal structure of the future recycling system, but provides a selection of good alternatives for potential locations of recycling plants.

Computers↗

Overview of informatics for high content screening.

With the growing use of high content screening (HCS) and analysis in drug discovery and systems biology, informatics has come to the forefront as a critical technology to effectively utilize the massive volumes of high content data and images being generated. Informatics technologies are required to transform HCS data and images into useful information and then into knowledge to drive decision making in an efficient and cost effective manner. In this chapter, we provide an overview of informatics tools and technologies for HCS, discuss some of the challenges of harnessing the huge and growing volumes of HCS data, and provide insight to help toward implementing or selecting, and utilizing a high content informatics solution to meet your organization's needs.

Computers↗