"epitools (epidemiology tools) is an R package for epidemiologic computing and graphics."
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The R-package ’surveillance’ is a framework for the development and the evaluation of outbreak detection algorithms in univariate and multivariate routine collected public health surveillance data. Hence, potential users are biostatisticians, epidemiologists and others working in applied infectious disease epidemiology. However, applications could just as well originate from environmetrics, reliability engineering, econometrics or social sciences.
DiagnosisMed is a package to analyze data from diagnostic test accuracy evaluating health conditions. It is being built to be used by health professionals. This package is able to estimate sensitivity and specificity from categorical and continuous test results including some evaluations of indeterminate results, or compare different categorical tests, and estimate reasonble cut-offs of tests and display it in a way commonly used by health professionals. No graphical interface is avalible yet. Partners are most welcome.
This package contains elementary tools for analysis of common epidemiological problems, ranging from sample size estimation, through 2x2 contingency table analysis and basic measures of agreement (kappa, sensitivity/specificity).
Appropriate print and summary statements are also written to facilitate interpretation wherever possible.
This package is a work in progress, so any comments or suggestions would be appreciated. Source code is commented throughout to facilitate modification. The target audience includes graduate students in various epi/biostatistics courses.
Functions making R easy for epidemiological calculation.
Datasets from Dbase (.dbf), Stata (.dta), SPSS(.sav), EpiInfo(.rec) and Comma separated value (.csv) formats as well as R data frames can be processed to do make several epidemiological calculations.
A package for analysing epidemiological data. Contains functions for directly and indirectly adjusting measures of disease frequency, quantifying measures of association on the basis of single or multiple strata of count data presented in a contingency table, and computing confidence intervals around incidence risk and incidence rate estimates. Miscellaneous functions for use in meta-analysis, diagnostic test interpretation, and sample size calculations.
Adherence is defined as "the extent to which a person’s behavior coincides with medical or health
advice", which is very important, for both clinical researchers and physicians, to identify the treatment
effect of a specific medication(s).
Bioconductor is an open source, open development software project to provide tools for the analysis and comprehension of high-throughput genomic data. It is based primarily on the R programming language.
The Bioconductor release version is updated twice each year, and is appropriate for most users. There is also a development version, to which new features and packages are added prior to incorporation in the release. A large number of meta-data packages provide pathway, organism, microarray and other annotations.
The openCDMS project is a community effort to develop a robust, commercial-grade, full-featured and open source clinical data management system for studies and trials. The philosophy behind openCDMS is to enable clinical researchers to manage the full life cycle of their clinical research project, from design through to archiving, without any specialist knowledge of databases or IT systems.
openCDMS provides purpose built visual tools the enable clinical researchers to design, develop, implement, and manage large scale, multi-centre studies and trials quickly and easily.