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MissMech (version 1.0.2)

Testing Homoscedasticity, Multivariate Normality, and Missing Completely at Random

Description

To test whether the missing data mechanism, in a set of incompletely observed data, is one of missing completely at random (MCAR). For detailed description see Jamshidian, M. Jalal, S., and Jansen, C. (2014). "MissMech: An R Package for Testing Homoscedasticity, Multivariate Normality, and Missing Completely at Random (MCAR)," Journal of Statistical Software, 56(6), 1-31. URL http://www.jstatsoft.org/v56/i06/.

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Version

Install

install.packages('MissMech')

Monthly Downloads

653

Version

1.0.2

License

GPL (>= 2)

Maintainer

Mortaza Jamshidian

Last Published

April 14th, 2015

Functions in MissMech (1.0.2)

Ddf

Hessian of the observed datat Multivariate Normal Log-Likelihood with Incomplete Data
agingdata

Montpetit and Bergeman Longitudinal Study on Aging Data
TestMCARNormality

Testing Homoscedasticity, Multivariate Normality, and Missing Completely at Random
AndersonDarling

K-Sample Anderson Darling Test
OrderMissing

Order Missing Data Pattern
DelLessData

Removes groups with identical missing data patterns having at most a given number of cases
Hawkins

Test Statistic for the Hawkins Homoscedasticity Test
TestUNey

Test of Goodness of Fit (Uniformity)
LegNorm

Evaluating Legendre's Polynomials of Degree 1, 2, 3, or 4
MissMech-package

Testing Homoscedasticity, Multivariate Normality, and Missing Completely at Random
Impute

Parametric and Non-Parameric Imputation
Mls

ML Estimates of Mean and Covariance Based on Incomplete Data