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Abstract
Introduction: Meta analysis is a systematic, quantitative approach consisting of statistical methods which combine results from independent studies for synthesizing conclusions in medical and other areas of research. Its prevalence and acceptance in the scientific literature has increased dramatically during the past decade, especially in clinical trials for evaluating therapeutic effectiveness and making subsequent clinical recommendations. Recently there has been increased need and interest in applying meta analysis methods to epidemiologic studies and other public health research. To date, there have been few commercially available statistical software packages which perform meta analysis. Rather, most individuals have developed their own computer code or modified existing softwares for their research needs.
Objective: Here we describe EPIMETA, a new statistical software codeveloped by CDC for application to epidemiologic research data. A companion manual, including an overview of meta analysis methods and a tutorial for using EPIMETA, is also described.
Discussion: EPIMETA implements a systematic approach comprised of quantitative methods to analyze epidemiologic and other public health data. It focuses on statistical procedures to estimate weighted averages for parameters of interest, such as relative risks or odds ratios. The analysis procedure performs 'within' study and 'among' studies analyses, and includes options for transformations, selection of fixed or random effects model, and inclusion of fixed or estimated intercept. The software designates outlier studies and provides a series of diagnostic graphics portraying results and characterizing contributions of individual studies. The program is DOS-based, but features a Windows-like interface to facilitate data entry, file manipulation, and subgroup analysis. EPIMETA was designed to integrate with EpiInfo, a CDC-developed data management and analysis software familiar to many public health officials. EPIMETA is written in C++ and requires an IBM-compatible computer, 386 processor, DOS 3.1, 600k RAM, 2Mb hard disk space, and EpiInfo installed on the system.
Objective: Here we describe EPIMETA, a new statistical software codeveloped by CDC for application to epidemiologic research data. A companion manual, including an overview of meta analysis methods and a tutorial for using EPIMETA, is also described.
Discussion: EPIMETA implements a systematic approach comprised of quantitative methods to analyze epidemiologic and other public health data. It focuses on statistical procedures to estimate weighted averages for parameters of interest, such as relative risks or odds ratios. The analysis procedure performs 'within' study and 'among' studies analyses, and includes options for transformations, selection of fixed or random effects model, and inclusion of fixed or estimated intercept. The software designates outlier studies and provides a series of diagnostic graphics portraying results and characterizing contributions of individual studies. The program is DOS-based, but features a Windows-like interface to facilitate data entry, file manipulation, and subgroup analysis. EPIMETA was designed to integrate with EpiInfo, a CDC-developed data management and analysis software familiar to many public health officials. EPIMETA is written in C++ and requires an IBM-compatible computer, 386 processor, DOS 3.1, 600k RAM, 2Mb hard disk space, and EpiInfo installed on the system.