Rfunction_include_argument_values
Utility Functions for Writing R Functions
R Utilities: Removing CF Line Endings
Calculation of Groupwise Descriptive Statistics for Matrices
Wald Test for Nested Multiply Imputed Datasets
Example Datasets for miceadds Package
Small-Scale Dataset for Testing Purposes (Moderate Number of Cases,
Many Variables)
Kernel PLS Regression
Converts a jomo Data Frame in Long Format into a List of Datasets or an Object
of Class mids
R Utilities: Copy of an Rcpp File
Simulating Univariate Data from Fleishman Power Normal Transformations
mice.impute.2l.contextual.pmm
Imputation by Predictive Mean Matching or Normal Linear Regression
with Contextual Variables
R Utilities: R Session Information
Functions for Analysis of Nested Multiply Imputed Datasets
R Utilities: Evaluates a String as an Expression in R
Cluster Robust Standard Errors for Linear Models and General Linear Models
R Utilities: Loading a Package or Installation of a Package if Necessary
Imputation of a Variable Using Probabilistic Hot Deck Imputation
Datasets from Allison's Missing Data Book
R Utilities: Vector Based Versions of grep
Stringing Variable Names with Line Breaks
Moves Files from One Directory to Another Directory
Plausible Value Imputation Using a Known Measurement Error Variance
(Based on Classical Test Theory)
mice.impute.2l.latentgroupmean.ml
Imputation of Latent and Manifest Group Means for Multilevel Data
R Utilities: Loading/Reading Data Files using miceadds
Datasets from Grahams Missing Data Book
Dataset Internet
Some Functionality for Strings and File Names
Large-scale Dataset for Testing Purposes (Many Cases, Few Variables)
Standardization of a Matrix
Combination of F Statistics for Multiply Imputed Datasets Using a
Chi Square Approximation
Converting an Object of class amelia
Rhat Convergence Statistic of a mice
Imputation
Imputation using Partial Least Squares for Dimension Reduction
Imputation by Tricube Predictive Mean Matching
Indicator Function for Analyzing Coverage
Imputation of a Categorical Variable Using Multivariate Predictive
Mean Matching
Imputation by Predictive Mean Matching (in miceadds )
R Utilities: Include an Index to a Data Frame
Creates Imputed Dataset from a mids.nmi
or mids.1chain
Object
Imputation by Weighted Predictive Mean Matching or Weighted Normal Linear Regression
Export mids
object to MLwiN
Groupwise Imputation Function
mice.impute.2lonly.function
Imputation at Level 2 (in miceadds )
Sum Preserving Rounding
Datasets from Enders' Missing Data Book
Statistical Inference for Fixed and Random Structure for Fitted Models
in lme4
Two-Way Imputation
R Utilities: Loading Rdata
Files in a Convenient Way
Converting a List of Multiply Imputed Data Sets into a mids
Object
Some Multivariate Descriptive Statistics for Weighted Data in miceadds
Converting a Nested List into a List (and Vice Versa)
Pooling for Nested Multiple Imputation
Substantive Model Compatible Multiple Imputation (Single Level)
Analysis of Variance for Multiply Imputed Data Sets (Using the \(D_2\) Statistic)
mice.impute.plausible.values
Plausible Value Imputation using Classical Test Theory and
Based on Individual Likelihood
Using a synthpop Synthesizing Method in the mice Package
Inference for Correlations and Covariances for Multiply Imputed Datasets
Creates Objects of Class datlist
or nested.datlist
Imputation Using a Fixed Vector
Combination of Chi Square Statistics of Multiply Imputed Datasets
MCMC Estimation for Mixed Effects Model
R Utilities: Scan a Character Vector
Nested Multiple Imputation
R Utilities: Source all R or Rcpp Files within a Directory
Synthesizing Method for Fixed Values by Design in synthpop
Simulating Normally Distributed Data
Imputation of a Continuous or a Binary Variable From a Two-Level Regression Model
using lme4 or blme
Cohen's d Effect Size for Missingness Indicators
Multiple Imputation by Chained Equations using One Chain
Multilevel Imputation Using lme4
Subsetting Multiply Imputed Datasets and Nested Multiply Imputed Datasets
Principal Component Analysis with Ridge Regularization
Utility Functions for Working with lme4 Formula Objects
Simulation of Multivariate Linearly Related Non-Normal Variables
R Utilities: Formatting R Output on the R Console
Arguments for mice::mice
Function
Defunct miceadds Functions
Generation of Synthetic Data Utilizing Data Augmentation
Synthesizing Method for synthpop Using a Formula Interface
tools:::Rd_package_title("miceadds")
Automatic Determination of a Visit Sequence in mice
Writing a Data Frame into SPSS Format Using PSPP Software
mice.impute.imputeR.lmFun
Wrapper Function to Imputation Methods in the imputeR Package
Statistical Inference for Multiply Imputed Datasets
Utility Functions in miceadds
Imputation of a Linear Model by Bayesian Bootstrap
Using a mice Imputation Method in the synthpop Package
Wrapper Function to Imputation Methods in the simputation Package
Constructs Synthetic Dataset with mice Imputation Methods
Descriptive Statistics for a Vector or a Data Frame
R Utilities: Rounding DIN 1333 (Kaufmaennisches Runden)
R Utilities: Various Strings Representing System Time
R Utilities: String Paste Combined with expand.grid
Converting a mids
, mids.1chain
or mids.nmi
Object in a Dataset List
R Utilities: Save a Data Frame in Rdata
Format
Reading and Writing Files in Fixed Width Format
R Utilities: Saving/Writing Data Files using miceadds
Adding a Standardized Variable to a List of Multiply Imputed Datasets or a
Single Datasets
Evaluates an Expression for (Nested) Multiply Imputed Datasets
Write a List of Multiply Imputed Datasets
Export Multiply Imputed Datasets from a mids
Object