Project Wizard

You can use the category filters given on the right sidebar to narrow down your search results.

The 'surveillance' R Package

Rating: 
No votes yet

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.

GNU Octave

Rating: 
Your rating: None Average: 4.5 (2 votes)

GNU Octave is a high-level language, primarily intended for numerical computations. It provides a convenient command line interface for solving linear and nonlinear problems numerically, and for performing other numerical experiments using a language that is mostly compatible with Matlab. It may also be used as a batch-oriented language.

The 'DiagnosisMed' R Package

Rating: 
Your rating: None Average: 4 (1 vote)

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.

The 'epi' R Package

Rating: 
No votes yet

The Epi package is mainly focused on "classical" chronic disease epidemiology. The package has grown out of the course Statistical Practice in Epidemiology using R.

The 'epibasix' R Package

Rating: 
Your rating: None Average: 5 (1 vote)

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.

The 'epicalc' R Package

Rating: 
Your rating: None Average: 5 (2 votes)

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.

The 'epiR' R Package

Rating: 
Your rating: None Average: 1 (3 votes)

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.

Gwyddion

Rating: 
No votes yet

Gwyddion is a modular program for SPM (scanning probe microscopy) data visualization and analysis. Primarily it is intended for analysis of height fields obtained by scanning probe microscopy techniques (AFM, MFM, STM, SNOM/NSOM), however it can be generally used for any other height field and image analysis, for instance for analysis of profilometry data.

It aims to provide multiplatform modular program for 2D data analysis that could be easily extended by modules and plug-ins.

The 'medAdherence' R Package

Rating: 
Your rating: None Average: 1 (1 vote)

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).

Pages