
SAS/STAT
 Referenced in 343 articles
[sw18788]
 analyses, including analysis of variance, regression, categorical data analysis, multivariate analysis, survival analysis, psychometric analysis...

MICE
 Referenced in 82 articles
[sw09315]
 normal), binary data (logistic regression), unordered categorical data (polytomous logistic regression) and ordered categorical data...

np
 Referenced in 63 articles
[sw10543]
 continuous, discrete, and categorical data often found in applied settings. Datadriven methods of bandwidth...

Mplus
 Referenced in 295 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 92 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...

vcd
 Referenced in 20 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...

catdata
 Referenced in 22 articles
[sw27750]
 package catdata: Categorical Data. This Rpackage contains examples from the book ”Regression for Categorical...

Surveillance
 Referenced in 23 articles
[sw00932]
 phenomena. This includes count, binary and categorical data time series as well as continuoustime...

MULTIMIX
 Referenced in 29 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...

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...

categorical
 Referenced in 5 articles
[sw13141]
 Analysis of categorical data with R. The book presents a modern account of categorical data...

REALCOM
 Referenced in 7 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 online...

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

SpectralCAT
 Referenced in 7 articles
[sw18794]
 SpectralCAT: Categorical spectral clustering of numerical and nominal data. Data clustering is a common technique ... automatically transform the highdimensional 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...

missForest
 Referenced in 5 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 nonlinear relations...

LMest
 Referenced in 5 articles
[sw11736]
 Latent Markov model for longitudinal categorical data...

DIVCLUST
 Referenced in 5 articles
[sw02736]
 designed for either numerical or categorical data. Like the Ward agglomerative hierarchical clustering algorithm...

PROC CATMOD
 Referenced in 3 articles
[sw12082]
 CATMOD procedure performs categorical data modeling of data that can be represented by a contingency ... procedure provides a wide variety of categorical data analyses, many of which are generalizations...