
REALCOM
 Referenced in 7 articles
[sw18415]
 assumption that the data are missing at random. However, many medical and social datasets...

MissMech
 Referenced in 3 articles
[sw24416]
 Testing Homoscedasticity, Multivariate Normality, and Missing Completely at Random. To test whether the missing data ... observed data, is one of missing completely at random (MCAR). For detailed description see Jamshidian ... Testing Homoscedasticity, Multivariate Normality, and Missing Completely at Random (MCAR),” Journal of Statistical Software...

missForest
 Referenced in 5 articles
[sw19483]
 package missForest: Nonparametric Missing Value Imputation using Random Forest. The function ’missForest’ in this package ... missing values particularly in the case of mixedtype data. It uses a random forest...

ice
 Referenced in 4 articles
[sw24700]
 with missing covariate data under a missingatrandom assumption. We describe ice, an implementation...

VarSelLCM
 Referenced in 3 articles
[sw15183]
 values by assuming that values are missing at random. The onedimensional marginals ... This package also performs the imputation of missing values...

PROC CALIS
 Referenced in 1 article
[sw12071]
 used. If your data sets contain random missing data, the full information maximum likelihood (FIML...

eigenmodel
 Referenced in 1 article
[sw26199]
 assumption that the data are missing at random. The marginal distribution of the relational data...

experiment
 Referenced in 1 article
[sw24908]
 randomized experiments with noncompliance, and randomized experiments with missing data...

BradleyTerry2
 Referenced in 15 articles
[sw09554]
 quasilikelihood (for models which involve a random effect), or by biasreduced maximum likelihood ... simple and efficient approach to handling missing covariate data, and suitablydefined residuals for diagnostic...

sanon
 Referenced in 1 article
[sw24138]
 Whitney estimator addresses the comparison between two randomized groups for a strictly ordinal response variable ... measurements and these can have missing completely at random (MCAR) data. Nonparametric covariance adjustment...

speff2trial
 Referenced in 0 articles
[sw15614]
 treatment effect in a 2group randomized clinical trial with a quantitative, dichotomous, or right ... unbiased estimation when the endpoint is missing at random...

rrp
 Referenced in 2 articles
[sw25704]
 Data Matching. Random Recursive Partitiong and Rankbased proximities for data matching, missing data imputation...

mirf
 Referenced in 2 articles
[sw26718]
 random forests (MIRF) for unobservable, highdimensional data. This package applies a combination of missing ... modelling traithaplotype associations via the Random Forest algorithm. The EM algorithm is implemented...

SAPPER
 Referenced in 4 articles
[sw18894]
 large database graph with (possible) missing edges. The SAPPER method is proposed to solve this ... index, SAPPER takes advantage of pregenerated random spanning trees and a carefully designed graph...

ArpEgg
 Referenced in 1 article
[sw14213]
 solve this, most arpeggiators have a “random” setting. While this produces more complex results ... musician is extremely hitandmiss, forgoing any form of control over the process itself ... artist must rely on luck that a random sequence will be suitable. Neither extreme...

MissingDataGUI
 Referenced in 2 articles
[sw23665]
 Provides numeric and graphical summaries for the missing values from both categorical and quantitative variables ... including the univariate imputations like fixed or random values, multivariate imputations like the nearest neighbors...

OSWALD
 Referenced in 5 articles
[sw26003]
 different dropout mechanisms: completely random dropout (CRD), random dropout (RD) and informative dropout ... less bias with OSWALD under the ID missing data assumption than under...

metagear
 Referenced in 0 articles
[sw18370]
 gaps in incomplete or missing study parameters; generation of random effects sizes for Hedges...

bild
 Referenced in 1 article
[sw24688]
 observations from a given individual and a random intercept term. Estimation is via maximization ... exact likelihood of a suitably defined model. Missing values and unbalanced data are allowed, with...