• SAS/STAT

  • Referenced in 393 articles [sw18788]
  • analyses, including analysis of variance, regression, categorical data analysis, multivariate analysis, survival analysis, psychometric analysis...
  • MICE

  • Referenced in 110 articles [sw09315]
  • normal), binary data (logistic regression), unordered categorical data (polytomous logistic regression) and ordered categorical data...
  • np

  • Referenced in 88 articles [sw10543]
  • continuous, discrete, and categorical data often found in applied settings. Data-driven methods of bandwidth...
  • Mplus

  • Referenced in 321 articles [sw06511]
  • with either observed or unobserved heterogeneity, and data that contain missing values. Analyses ... variables that are continuous, censored, binary, ordered categorical (ordinal), unordered categorical (nominal), counts, or combinations ... capabilities for Monte Carlo simulation studies, where data can be generated and analyzed according...
  • RCV1

  • Referenced in 106 articles [sw07279]
  • archive of over 800,000 manually categorized newswire stories recently made available by Reuters ... purposes. Use of this data for research on text categorization requires a detailed understanding...
  • catdata

  • Referenced in 29 articles [sw27750]
  • package catdata: Categorical Data. This R-package contains examples from the book ”Regression for Categorical...
  • vcd

  • Referenced in 21 articles [sw04543]
  • package vcd: Visualizing Categorical Data , Visualization techniques, data sets, summary and inference procedures aimed particularly ... categorical data. Special emphasis is given to highly extensible grid graphics. The package was inspired ... book ”Visualizing Categorical Data” by Michael Friendly...
  • missForest

  • Referenced in 26 articles [sw19483]
  • trained on the observed values of a data matrix to predict the missing values ... used to impute continuous and/or categorical data including complex interactions and non-linear relations...
  • Surveillance

  • Referenced in 26 articles [sw00932]
  • phenomena. This includes count, binary and categorical data time series as well as continuous-time...
  • MULTIMIX

  • Referenced in 33 articles [sw03250]
  • designed to cluster multivariate data that have categorical and continuous variables and that possibly contain...
  • VCD

  • Referenced in 8 articles [sw25927]
  • Visualizing Categorical Data. Categorical data consists of variables whose values comprise a set of discrete ... graphical methods than commonly used for quantitative data. The focus of this book ... designed to reveal patterns of relationships among categorical variables...
  • categorical

  • Referenced in 8 articles [sw13141]
  • Analysis of categorical data with R. The book presents a modern account of categorical data...
  • LEM

  • Referenced in 11 articles [sw12167]
  • general program for the analysis of categorical data...
  • MacSpin

  • Referenced in 10 articles [sw14078]
  • user to transform, edit, and categorize data as patterns in the display indicate. MacSpin also...
  • ProbCD

  • Referenced in 5 articles [sw20338]
  • contingency tables, a type of categorical data analysis known in this field as enrichment (also ... package to deal with probabilistic categorical data analysis, ProbCD, that does not require a static ... Bernoulli Scheme stochastic process given the categorization probabilities. An on-line interface was created ... address the issue of uncertainty in categorical data analysis. In particular, concerning the enrichment analysis...
  • REALCOM

  • Referenced in 8 articles [sw18415]
  • observed data, under the assumption that the data are missing at random. However, many medical ... imputation, and handles ordinal and unordered categorical data appropriately. It is freely available on-line...
  • LMest

  • Referenced in 7 articles [sw11736]
  • Latent Markov model for longitudinal categorical data...
  • vcdExtra

  • Referenced in 6 articles [sw09553]
  • complement the ’vcd’ package for Visualizing Categorical Data and the ’gnm’ package for Generalized Nonlinear...
  • SpectralCAT

  • Referenced in 8 articles [sw18794]
  • SpectralCAT: Categorical spectral clustering of numerical and nominal data. Data clustering is a common technique ... automatically transform the high-dimensional input data into categorical values. This is done by discovering ... clustering via dimensionality reduction of the transformed data is applied. This is achieved by automatic...
  • blockcluster

  • Referenced in 7 articles [sw17883]
  • blockcluster. Coclustering Package for Binary, Categorical, Contingency and Continuous Data-Sets. Simultaneous clustering of rows ... important technique in two way data analysis. It consists of estimating a mixture model which ... cluster binary, contingency, continuous and categorical data-sets. It also provides utility functions to visualize...