• SAS/STAT

  • Referenced in 418 articles [sw18788]
  • analyses, including analysis of variance, regression, categorical data analysis, multivariate analysis, survival analysis, psychometric analysis...
  • Mplus

  • Referenced in 339 articles [sw06511]
  • analysis of both cross-sectional and longitudinal data, single-level and multilevel data, data that ... 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...
  • categorical

  • Referenced in 9 articles [sw13141]
  • Analysis of categorical data with ... book presents a modern account of categorical data analysis using the popular R software...
  • LEM

  • Referenced in 12 articles [sw12167]
  • general program for the analysis of categorical data...
  • ProbCD

  • Referenced in 5 articles [sw20338]
  • ProbCD: enrichment analysis accounting for categorization uncertainty. As in many other areas of science, systems ... 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 ... address the issue of uncertainty in categorical data analysis. In particular, concerning the enrichment analysis...
  • extracat

  • Referenced in 3 articles [sw13273]
  • package extracat: Categorical Data Analysis and Visualization. Categorical Data Analysis and Visualization...
  • mvis

  • Referenced in 10 articles [sw37353]
  • function of several covariates, each with complete data. micombine fits a wide variety of regression ... rules, and supports survival analysis models (stcox and streg), categorical data models, generalized linear models...
  • AFMULT

  • Referenced in 21 articles [sw08201]
  • Multiple Factor Analysis (MFA) studies several groups of variables (numerical and/or categorical) defined ... individuals. MFA approaches this kind of data according to many points of view already used ... others methods as: factor analysis in which groups of variables are weighted, canonical analysis, Procrustes...
  • missMDA

  • Referenced in 15 articles [sw08142]
  • with/in multivariate data analysis (principal component methods). Imputation of incomplete continuous or categorical datasets; Missing...
  • ACD

  • Referenced in 1 article [sw32781]
  • package ACD: Categorical data analysis with complete or missing responses. Categorical data analysis with complete...
  • Latent GOLD

  • Referenced in 93 articles [sw11673]
  • categorical, LC modeling differs from more traditional latent variable approaches such as factor analysis, structural ... continuous latent variables. Latent class (LC) analysis was originally introduced by Lazarsfeld ... seek to separate out or ’un-mix’ data that is assumed to arise...
  • PCAmixdata

  • Referenced in 4 articles [sw08547]
  • Multivariate analysis of mixed data: The PCAmixdata R package. Mixed data type arise when observations ... described by a mixture of numerical and categorical variables. The R package PCAmixdata ... extends standard multivariate analysis methods to incorporate this type of data. The key techniques included ... categorical variables), PCArot (rotation in PCAmix) and MFAmix (multiple factor analysis with mixed type data...
  • EXCDA

  • Referenced in 1 article [sw22550]
  • EXCDA: an enhanced categorical data analysis package...
  • NominalLogisticBiplot

  • Referenced in 1 article [sw32659]
  • package NominalLogisticBiplot: Biplot representations of categorical data. Analysis of a matrix of polytomous items using...
  • clustrd

  • Referenced in 4 articles [sw17529]
  • clustering of continuous or categorical data. For continuous data, the package contains implementations of factorial ... combine principal component analysis with K-means clustering. For categorical data, the package provides ... href=”http://dx.doi.org/10.1007/s00180-012-0329-x”>doi:10.1007/s00180-012-0329-x>) and Cluster Correspondence Analysis (van de Velden, Iodice D’Enza...
  • scrime

  • Referenced in 1 article [sw11398]
  • High-Dimensional Categorical Data such as SNP Data. Tools for the analysis of high-dimensional ... data. But most of the functions can also be applied to other types of categorical...
  • PROC CATMOD

  • Referenced in 3 articles [sw12082]
  • CATMOD procedure performs categorical data modeling of data that can be represented by a contingency ... linear modeling, logistic regression, and repeated measurement analysis. PROC CATMOD uses the following estimation methods ... categorical data analyses, many of which are generalizations of continuous data analysis methods. For example...
  • SpectralCAT

  • Referenced in 8 articles [sw18794]
  • SpectralCAT: Categorical spectral clustering of numerical and nominal data. Data clustering is a common technique ... data analysis, which is used in many fields, including machine learning, data mining, customer segmentation ... clustering of one data type (numerical or nominal) or with mix data type (numerical ... automatically transform the high-dimensional input data into categorical values. This is done by discovering...
  • gcmr

  • Referenced in 27 articles [sw07433]
  • errors. Any kind of continuous, discrete and categorical responses is allowed. Dependence is conveniently modelled ... continuous setting numerical approximations are used. Residual analysis and a specification test are suggested ... called gcmr. Illustrations include simulations and real data applications regarding time series, cross-design data...
  • ECCLAT

  • Referenced in 2 articles [sw02548]
  • from large categorical data (which is an usual situation, e.g., web data analysis). Our method...