• VIM

  • Referenced in 22 articles [sw06776]
  • quality of imputation can be visually explored using various univariate, bivariate, multiple and multivariate plot...
  • Qtools

  • Referenced in 4 articles [sw27689]
  • quantiles of discrete variables, quantile-based multiple imputation, and restricted quantile regression. A vignette...
  • runmlwin

  • Referenced in 4 articles [sw23864]
  • multilevel measurement error models and multilevel multiple imputation models...
  • smcfcs

  • Referenced in 2 articles [sw40853]
  • package smcfcs: Multiple Imputation of Covariates by Substantive Model Compatible Fully Conditional Specification. Implements multiple ... imputation of missing covariates by Substantive Model Compatible Fully Conditional Specification. This ... modification of the popular FCS/chained equations multiple imputation approach, and allows imputation of missing covariate...
  • mitml

  • Referenced in 2 articles [sw21012]
  • package mitml: Tools for Multiple Imputation in Multilevel Modeling. Provides tools for multiple imputation...
  • miceadds

  • Referenced in 2 articles [sw15857]
  • miceadds. Contains some auxiliary functions for multiple imputation which complements existing functionality ... high dimensional predictors, nested multiple imputation, and two-way imputation...
  • micemd

  • Referenced in 2 articles [sw35579]
  • package micemd: Multiple Imputation by Chained Equations with Multilevel Data. Addons for the ’mice’ package ... perform multiple imputation using chained equations with two-level data. Includes imputation methods dedicated...
  • inorm

  • Referenced in 2 articles [sw24701]
  • INORM: Stata module to perform multiple imputation using Schafer’s method. inorm is an implementation ... Schafer’s NORM program for multiple imputation based on the multivariate normal distribution (using...
  • mirf

  • Referenced in 2 articles [sw26718]
  • Package mirf: Multiple imputation and random forests (MIRF) for unobservable, high-dimensional data. This package ... applies a combination of missing haplotype imputation via the EM algorithm of Excoffier and Slatkin ... B.A.S. Nonyane and A.S. Foulkes (2007) Multiple imputation and random forests (MIRF) for unobservable high...
  • bmem

  • Referenced in 3 articles [sw07439]
  • analysis including listwise deletion, pairwise deletion, multiple imputation (MI), and a two-stage maximum likelihood...
  • MiPy

  • Referenced in 1 article [sw34052]
  • MiPy: a system for generating multiple imputations. Multiple imputation has proven to be a useful ... methodology in which missing values are imputed multiple times by draws from a (typically explicit ... lack of software for generating multiple imputations is a serious impediment to the routine adoption ... multiple imputation for handling missing data. Several groups have developed software for generating imputations, most...
  • Norm 2.03

  • Referenced in 1 article [sw08149]
  • Multiple Imputation with Norm 2.03. Multiple imputation is a simulation-based approach to the statistical ... analysis of incomplete data. In multiple imputation, each missing datum is replaced...
  • countimp

  • Referenced in 1 article [sw31551]
  • package countimp: Multiple Imputation of incomplete count data. Special data types like count data require ... imputation techniques. Yet, currently available multiple imputation tools are very limited with regard to count ... countimp package provides easy to use multiple imputation (MI) procedures for incomplete count data based...
  • MissingDataGUI

  • Referenced in 2 articles [sw23665]
  • imputations like the nearest neighbors and multiple imputations, and imputations conditioned on a categorical variable...
  • iVAR

  • Referenced in 2 articles [sw31224]
  • with sample means and variances, and multiple imputation ignoring time dependency. The results showed that...
  • miP

  • Referenced in 1 article [sw24122]
  • Multiple Imputation Plots - R package using mainstream CRAN packages mice, mi, Amelia,.. Plots to visualize ... datasets that were produced by Multiple Imputation. The goal is is to visualize MI objects ... provide a better understanding of the imputed data and to evaluate the MI process. This ... more easily compare their methods, notably Multiple Imputation. Currently, results from mice, mi, and Amelia...
  • MIDAS

  • Referenced in 2 articles [sw25534]
  • MIDAS: A SAS Macro for Multiple Imputation Using Distance-Aided Selection of Donors...
  • lori

  • Referenced in 1 article [sw30344]
  • using Side Information. Analysis, imputation, and multiple imputation of count data using covariates. LORI uses ... table. The package also contains a multiple imputation procedure...
  • migui

  • Referenced in 2 articles [sw24123]
  • user through the steps of multiple imputation and the analysis of completed data...
  • WinMICE

  • Referenced in 2 articles [sw24699]
  • program by Gert Jacobusse that implements multiple imputation under the linear mixed model...