It looks most of the material from epicalc has been moved into epiDisplay. Full ‘ epicalc’ package with data management functions is available at the author’s. Suggests Description Functions making R easy for epidemiological calculation. License GPL (>= 2) URL Epidemiological calculator. Contribute to cran/epicalc development by creating an account on GitHub.
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Epi Info is also not suitable for data manipulation for longitudinal studies and its regression analysis facilities cannot cope with repeated measures and multilevel modeling. Epicalc, an add-on package of R enables R to deal more easily with epidemiological data.
The epiDisplay package information says: National Center for Biotechnology InformationU. R is also a programming language with an extensive set of built-in functions. In R, a statistical analysis is normally done as a series of steps, with intermediate results being stored in objects.
Epicalc – Free Software Directory
The learning curve is typically longer than with a graphical user interface GUIalthough it is recognized that the effort is profitable and leads to better practice finer understanding of the analysis; command easily saved and replayed.
But for developing countries, the scenario did not change as expected because of the very high cost of the statistical packages. The other limitation is that, being an open source software, hackers can easily know about the weaknesses or loopholes of the software more easily than closed-source software and so it is more prone to bug attacks.
I just thought someone would know and indeed Ben Bolker provided the answer. Support Center Support Center. Package for data exploration and result presentation. Ben Bolker k 11 The steep learning of R is a serious disadvantage which if eased by the introduction of menu driven R can make it more popular among the non-mathematicians dealing with epidemiological data.
Analysis of Epidemiological Data using R and Epicalc
Apart from the packages which automatically come with R; there are more than packages available at CRAN. R is provided with a command line interface CLIwhich is the preferred user interface for power users because it allows direct control on calculations and it is flexible. The R Environment R is an integrated suite of software facilities for data manipulation, calculation and graphical display.
For basic biostatistical and epidemiological purposes Epicalc package is sufficient to start with and then to go on for other packages as and when required. It was first launched as a Disk Operating System DOS based version, which was command driven epifalc difficult to learn by the medical researchers.
The ‘epicalc’ R Package
Full ‘epicalc’ package with data management functions is available at the author’s repository. So depending on the type of statistical analytical techniques, one can download the package required. One can use the nearest with respect to geographical location CRAN mirror to minimize network load.
r-cran-epicalc package : Ubuntu
Epivalc includes An effective data handling and storage facility. With the introduction of softwares for statistical computations, things changed and data analysis came to be thought of something within the realm of possibility by the medical researchers. Epicalc, written by Virasakdi Chongsuvivatwong of Prince of Songkla University, Hat Yai, Thailand has been well accepted by members of the R core-team and the package is downloadable from CRAN which is mirrored by 69 academic institutes in 29 countries.
The main advantage of using this package is that it gives rise to display which is more understandable by most epidemiologists. Why not ask them? As the dataset is usually large in epidemiology, calculating even simple statistics like mean or standard deviation is quite cumbersome to be done manually.
R can be extended via packages. Being free of cost, it is surely a boon for researchers in developing countries and resource scarce institutions The quality of this software in terms of handling large datasets, having hundreds of functions with ever increasing number of add on packages and the neat outputs is also an advantage.
Softwares in Data Analysis With the introduction of softwares for statistical computations, things changed and data analysis came to be thought of something within the realm of possibility by the medical researchers. But no further explanation is given. Conclusions Being free of cost, it is surely a boon for researchers in developing countries and resource scarce institutions The quality of this software in terms of handling large datasets, having hundreds of functions with ever increasing number of add on packages and the neat outputs is also an advantage.
Formerly available versions can be obtained from the archive. Author information Article notes Copyright and License information Disclaimer. However, good knowledge of the language is required.