nparcomp: An R Software Package for Nonparametric Multiple Comparisons and Simultaneous Confidence Intervals
By Frank Konietschke, Marius Placzek, Frank Schaarschmidt, Ludwig A. Hothorn. 2015
318 citations recorded by the source corpus.
One-way layouts, i.e., a single factor with several levels and multiple observations at each level, frequently arise in various fields. Usually not only a global hypothesis is of interest but also multiple comparisons between the different treatment levels. In most practical situations, the distribution of observed data is unknown and there may exist a number of atypical measurements and outliers. Hence, use of parametric and semiparametric procedures that impose restrictive distributional assumptions on observed samples becomes questionable. This, in turn, emphasizes the demand on statistical procedures that enable us to accurately and reliably analyze one-way layouts with minimal conditions on available data. Nonparametric methods offer such a possibility and thus become of particular practical importance. In this article, we introduce a new R package nparcomp which provides an easy and user-friendly access to rank-based methods for the analysis of unbalanced one-way layouts. It provides procedures performing multiple comparisons and computing simultaneous confidence intervals for the estimated effects which can be easily visualized. The special case of two samples, the nonparametric Behrens-Fisher problem, is included. We illustrate the implemented procedures by examples from biology and medicine.
Subfields: Management Science and Operations Research, Statistics and Probability
View Paper: https://www.semanticscholar.org/paper/be4f84117f7b0c015054da582c9dc53f762d5fcd
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In Statistics and Probability
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Citations in the corpus
- The effect of flow speed and food size on the capture efficiency and feeding behaviour of the cold-water coral Lophelia pertusa (2016, methodology): “For significant effects, subsequent nonparametric multiple comparison procedure was performed with the R-language function nparcomp which is available in the nparcomp library (Konietschke et al., 2015).”