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R package krippendorffsalpha provides tools for measuring agreement using Krippendorffs Alpha coefficient, a well-known nonparametric measure of agreement (also called inter-rater reliability and various other names). This article first develops Krippendorffs Alpha in a natural way, and situates Alpha among statistical procedures. Then the usage of package krippendorffsalpha is illustrated via analyses of two datasets, the latter of which was collected during an imaging study of hip cartilage. The package permits users to apply the Alpha methodology using built-in distance functions for the nominal, ordinal, interval, or ratio levels of measurement. User-defined distance functions are also supported. The fitting function can accommodate any number of units, any number of coders, and missingness. Bootstrap inference is supported, and the bootstrap computation can be carried out in parallel.
The rstap package implements Bayesian spatial temporal aggregated predictor models in R using the probabilistic programming language Stan. A variety of distributions and link functions are supported, allowing users to fit this extension to the genera
The R package optimall offers a collection of functions that efficiently streamline the design process of sampling in surveys ranging from simple to complex. The packages main functions allow users to interactively define and adjust strata cut points
Process data refer to data recorded in the log files of computer-based items. These data, represented as timestamped action sequences, keep track of respondents response processes of solving the items. Process data analysis aims at enhancing educatio
This document describes the R package UBL that allows the use of several methods for handling utility-based learning problems. Classification and regression problems that assume non-uniform costs and/or benefits pose serious challenges to predictive
R is a programming language and environment that is a central tool in the applied sciences for writing program. Its impact on the development of modern statistics is inevitable. Current research, especially for big data may not be done solely using R