GroupMean               Calculation of Groupwise Descriptive Statistics
                        for Matrices
NMIwaldtest             Wald Test for Nested Multiply Imputed Datasets
NestedImputationList    Functions for Analysis of Nested Multiply
                        Imputed Datasets
Reval                   R Utilities: Evaluates a String as an
                        Expression in R
Rfunction_include_argument_values
                        Utility Functions for Writing R Functions
Rhat.mice               Rhat Convergence Statistic of a 'mice'
                        Imputation
Rsessinfo               R Utilities: R Session Information
VariableNames2String    Stringing Variable Names with Line Breaks
complete.mids.nmi       Creates Imputed Dataset from a 'mids.nmi' or
                        'mids.1chain' Object
crlrem                  R Utilities: Removing CF Line Endings
cxxfunction.copy        R Utilities: Copy of an 'Rcpp' File
data.allison            Datasets from Allison's _Missing Data_ Book
data.enders             Datasets from Enders' _Missing Data_ Book
data.graham             Datasets from Grahams _Missing Data_ Book
data.internet           Dataset Internet
data.largescale         Large-scale Dataset for Testing Purposes (Many
                        Cases, Few Variables)
data.ma                 Example Datasets for 'miceadds' Package
data.smallscale         Small-Scale Dataset for Testing Purposes
                        (Moderate Number of Cases, Many Variables)
datlist2mids            Converting a List of Multiply Imputed Data Sets
                        into a 'mids' Object
datlist_create          Creates Objects of Class 'datlist' or
                        'nested.datlist'
draw.pv.ctt             Plausible Value Imputation Using a Known
                        Measurement Error Variance (Based on Classical
                        Test Theory)
filename_split          Some Functionality for Strings and File Names
files_move              Moves Files from One Directory to Another
                        Directory
fleishman_sim           Simulating Univariate Data from Fleishman Power
                        Normal Transformations
grep.vec                R Utilities: Vector Based Versions of 'grep'
in_CI                   Indicator Function for Analyzing Coverage
index.dataframe         R Utilities: Include an Index to a Data Frame
jomo2datlist            Converts a 'jomo' Data Frame in Long Format
                        into a List of Datasets or an Object of Class
                        'mids'
kernelpls.fit2          Kernel PLS Regression
library_install         R Utilities: Loading a Package or Installation
                        of a Package if Necessary
lm.cluster              Cluster Robust Standard Errors for Linear
                        Models and General Linear Models
lmer_vcov               Statistical Inference for Fixed and Random
                        Structure for Fitted Models in 'lme4'
load.Rdata              R Utilities: Loading 'Rdata' Files in a
                        Convenient Way
load.data               R Utilities: Loading/Reading Data Files using
                        'miceadds'
ma.scale2               Standardization of a Matrix
ma.wtd.statNA           Some Multivariate Descriptive Statistics for
                        Weighted Data in 'miceadds'
ma_lme4_formula         Utility Functions for Working with 'lme4'
                        Formula Objects
ma_rmvnorm              Simulating Normally Distributed Data
mi.anova                Analysis of Variance for Multiply Imputed Data
                        Sets (Using the D_2 Statistic)
mi_dstat                Cohen's d Effect Size for Missingness
                        Indicators
mice.1chain             Multiple Imputation by Chained Equations using
                        One Chain
mice.impute.2l.binary   Imputation of a Continuous or a Binary Variable
                        From a Two-Level Regression Model using 'lme4'
                        or 'blme'
mice.impute.2l.contextual.pmm
                        Imputation by Predictive Mean Matching or
                        Normal Linear Regression with Contextual
                        Variables
mice.impute.2l.latentgroupmean.ml
                        Imputation of Latent and Manifest Group Means
                        for Multilevel Data
mice.impute.2lonly.function
                        Imputation at Level 2 (in 'miceadds')
mice.impute.bygroup     Groupwise Imputation Function
mice.impute.constant    Imputation Using a Fixed Vector
mice.impute.hotDeck     Imputation of a Variable Using Probabilistic
                        Hot Deck Imputation
mice.impute.imputeR.lmFun
                        Wrapper Function to Imputation Methods in the
                        'imputeR' Package
mice.impute.ml.lmer     Multilevel Imputation Using 'lme4'
mice.impute.plausible.values
                        Plausible Value Imputation using Classical Test
                        Theory and Based on Individual Likelihood
mice.impute.pls         Imputation using Partial Least Squares for
                        Dimension Reduction
mice.impute.pmm3        Imputation by Predictive Mean Matching (in
                        'miceadds')
mice.impute.rlm         Imputation of a Linear Model by Bayesian
                        Bootstrap
mice.impute.simputation
                        Wrapper Function to Imputation Methods in the
                        'simputation' Package
mice.impute.smcfcs      Substantive Model Compatible Multiple
                        Imputation (Single Level)
mice.impute.synthpop    Using a 'synthpop' Synthesizing Method in the
                        'mice' Package
mice.impute.tricube.pmm
                        Imputation by Tricube Predictive Mean Matching
mice.impute.weighted.pmm
                        Imputation by Weighted Predictive Mean Matching
                        or Weighted Normal Linear Regression
mice.nmi                Nested Multiple Imputation
mice_inits              Arguments for 'mice::mice' Function
miceadds-defunct        Defunct 'miceadds' Functions
miceadds-package        Some Additional Multiple Imputation Functions,
                        Especially for 'mice'
miceadds-utilities      Utility Functions in 'miceadds'
micombine.F             Combination of F Statistics for Multiply
                        Imputed Datasets Using a Chi Square
                        Approximation
micombine.chisquare     Combination of Chi Square Statistics of
                        Multiply Imputed Datasets
micombine.cor           Inference for Correlations and Covariances for
                        Multiply Imputed Datasets
mids2datlist            Converting a 'mids', 'mids.1chain' or
                        'mids.nmi' Object in a Dataset List
mids2mlwin              Export 'mids' object to MLwiN
ml_mcmc                 MCMC Estimation for Mixed Effects Model
nestedList2List         Converting a Nested List into a List (and Vice
                        Versa)
nnig_sim                Simulation of Multivariate Linearly Related
                        Non-Normal Variables
output.format1          R Utilities: Formatting R Output on the R
                        Console
pca.covridge            Principal Component Analysis with Ridge
                        Regularization
pool.mids.nmi           Pooling for Nested Multiple Imputation
pool_mi                 Statistical Inference for Multiply Imputed
                        Datasets
round2                  R Utilities: Rounding DIN 1333 (Kaufmaennisches
                        Runden)
save.Rdata              R Utilities: Save a Data Frame in 'Rdata'
                        Format
save.data               R Utilities: Saving/Writing Data Files using
                        'miceadds'
scale_datlist           Adding a Standardized Variable to a List of
                        Multiply Imputed Datasets or a Single Datasets
scan.vec                R Utilities: Scan a Character Vector
source.all              R Utilities: Source all R or 'Rcpp' Files
                        within a Directory
stats0                  Descriptive Statistics for a Vector or a Data
                        Frame
str_C.expand.grid       R Utilities: String Paste Combined with
                        'expand.grid'
subset_datlist          Subsetting Multiply Imputed Datasets and Nested
                        Multiply Imputed Datasets
sumpreserving.rounding
                        Sum Preserving Rounding
syn.constant            Synthesizing Method for Fixed Values by Design
                        in 'synthpop'
syn.formula             Synthesizing Method for 'synthpop' Using a
                        Formula Interface
syn.mice                Using a 'mice' Imputation Method in the
                        'synthpop' Package
syn_mice                Constructs Synthetic Dataset with 'mice'
                        Imputation Methods
systime                 R Utilities: Various Strings Representing
                        System Time
tw.imputation           Two-Way Imputation
visitSequence.determine
                        Automatic Determination of a Visit Sequence in
                        'mice'
with.mids.1chain        Evaluates an Expression for (Nested) Multiply
                        Imputed Datasets
write.datlist           Write a List of Multiply Imputed Datasets
write.fwf2              Reading and Writing Files in Fixed Width Format
write.mice.imputation   Export Multiply Imputed Datasets from a 'mids'
                        Object
write.pspp              Writing a Data Frame into SPSS Format Using
                        PSPP Software
