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Biostatistics - Open Access Articles | Open Access Journals
Journal of Biometrics & Biostatistics

Journal of Biometrics & Biostatistics

ISSN: 2155-6180

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Biostatistics - Open Access Articles

Biostatisticians have one of five main roles in the practice of public health. It’s their job to conduct quantitative research to identify health risks. They are biomedical researchers who focus on solving health problems at the community level. Biostatisticians follow the scientific method to test their hypotheses with empirical research. Biostatisticians conduct clinical trials, surveys, laboratory experiments, focus groups, field observations and case studies. The compilation and analysis of the data then come to draw proven conclusions. Biostatisticians use digital software, such as SPSS and SAS, to organize their results. Biostatisticians then share their statistically significant results. They can write a journal article, publish a book, make a presentation or teach at a university course. Biostatisticians have spread the word to help improve health outcomes. Arming people and public health workers with disease prevention tools is their mission.

The relative inequality index (RII) is a commonly used measure of the extent to which the occurrence of an outcome such as chronic disease or early death varies according to socioeconomic status or another contextual variable. The standard RII estimator only applies to the linear variation in incidence rates.

 

The general definition of the RII is introduced, alternative approaches to the point estimation are considered and a parametric bootstrap method is suggested for the construction of approximate confidence intervals. An estimate based on cubic splines adjusted by the maximum penalized probability is developed in detail, and the proposed approach naturally manages the adjustment commonly required for a "standardization" covariate such as age. Mortality rates in a large longitudinal study in England and Wales from 1996 to 2000 are analyzed to illustrate the different methods. A small simulation study explores the relative merits of different estimators. We note that the cubic spline approach considerably reduces the bias, to the detriment of a certain increase in the variance, when the variation in the incidence rates is non-linear.

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Citations: 3496

Journal of Biometrics & Biostatistics received 3496 citations as per Google Scholar report

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