We identify principles and practices for writing and publishing statistical software with maximum benefit to the scholarly community.

When respondents use the ordinal response categories of standard survey questions in different ways, the validity of analyses based on the resulting data can be biased. Anchoring vignettes is a survey design technique intended to correct for some of these problems. The anchors package in R...

A primary issue in industrial hygiene is the estimation of a worker's exposure to chemical, physical and biological agents. Mathematical modeling is increasingly being used as a method for assessing occupational exposures. However, predicting exposure in real settings is constrained by lack of...

This paper reviews the use of STAMP (Structural Time Series Analyser, Modeler and Predictor) for modeling time series data using state-space methods with unobserved components. STAMP is a commercial, GUI-based program that runs on Windows, Linux and Macintosh computers as part of the larger...

We introduce MCMCpack, an R package that contains functions to perform Bayesian inference using posterior simulation for a number of statistical models. In addition to code that can be used to fit commonly used models, MCMCpack also contains some useful utility functions, including some...

The population attributable fraction (PAF) is a useful measure for quantifying the impact of exposure to certain risk factors on a particular outcome at the population level. Recently, new model-based methods for the estimation of PAF and its confidence interval for different types of outcomes...

We give an overview of some of the software tools available in R, either as built- in functions or contributed packages, for the analysis of state space models. Several illustrative examples are included, covering constant and time-varying models for both univariate and multivariate time series....

poLCA is a software package for the estimation of latent class and latent class regression models for polytomous outcome variables, implemented in the R statistical computing environment. Both models can be called using a single simple command line. The basic latent class model is a finite...

Topic models allow the probabilistic modeling of term frequency occurrences in documents. The fitted model can be used to estimate the similarity between documents as well as between a set of specified keywords using an additional layer of latent variables which are referred to as topics. The R...