miceadds

Calculation of Groupwise Descriptive Statistics for Matrices

Wald Test for Nested Multiply Imputed Datasets

Functions for Analysis of Nested Multiply Imputed Datasets

R Utilities: Evaluates a String as an Expression in R

Utility Functions for Writing R Functions

Rhat Convergence Statistic of a mice Imputation

R Utilities: R Session Information

Stringing Variable Names with Line Breaks

Creates Imputed Dataset from a mids.nmi or mids.1chain Object

R Utilities: Removing CF Line Endings

R Utilities: Copy of an Rcpp File

Datasets from Allison's Missing Data Book

Datasets from Enders' Missing Data Book

Datasets from Grahams Missing Data Book

Dataset Internet

Large-scale Dataset for Testing Purposes (Many Cases, Few Variables)

Example Datasets for miceadds Package

Small-Scale Dataset for Testing Purposes (Moderate Number of Cases, Many Variables)

Converting a List of Multiply Imputed Data Sets into a mids Object

Creates Objects of Class datlist or nested.datlist

Plausible Value Imputation Using a Known Measurement Error Variance (Based on Classical Test Theory)

Some Functionality for Strings and File Names

Moves Files from One Directory to Another Directory

Simulating Univariate Data from Fleishman Power Normal Transformations

R Utilities: Vector Based Versions of grep

Indicator Function for Analyzing Coverage

R Utilities: Include an Index to a Data Frame

Converts a jomo Data Frame in Long Format into a List of Datasets or an Object of Class mids

Kernel PLS Regression

R Utilities: Loading a Package or Installation of a Package if Necessary

Cluster Robust Standard Errors for Linear Models and General Linear Models

Statistical Inference for Fixed and Random Structure for Fitted Models in lme4

R Utilities: Loading Rdata Files in a Convenient Way

R Utilities: Loading/Reading Data Files using miceadds

Standardization of a Matrix

Some Multivariate Descriptive Statistics for Weighted Data in miceadds

Utility Functions for Working with lme4 Formula Objects

Simulating Normally Distributed Data

Analysis of Variance for Multiply Imputed Data Sets (Using the D_2 Statistic)

Cohen's d Effect Size for Missingness Indicators

Multiple Imputation by Chained Equations using One Chain

Imputation by Predictive Mean Matching or Normal Linear Regression with Contextual Variables

Imputation of Latent and Manifest Group Means for Multilevel Data

Imputation at Level 2 (in miceadds)

Groupwise Imputation Function

Imputation Using a Fixed Vector

Imputation of a Variable with Grouped Values

Imputation of a Variable Using Probabilistic Hot Deck Imputation

Wrapper Function to Imputation Methods in the imputeR Package

Multilevel Imputation Using lme4

Plausible Value Imputation using Classical Test Theory and Based on Individual Likelihood

Imputation using Partial Least Squares for Dimension Reduction

Imputation by Predictive Mean Matching (in miceadds)

Imputation of a Linear Model by Bayesian Bootstrap

Wrapper Function to Imputation Methods in the simputation Package

Substantive Model Compatible Multiple Imputation (Single Level)

Using a synthpop Synthesizing Method in the mice Package

Imputation by Tricube Predictive Mean Matching

Imputation by Weighted Predictive Mean Matching or Weighted Normal Linear Regression

Nested Multiple Imputation

Imputation of a Continuous or a Binary Variable From a Two-Level Regression Model using lme4 or blme

Arguments for mice::mice Function

Defunct miceadds Functions

Some Additional Multiple Imputation Functions, Especially for 'mice'

Utility Functions in miceadds

Combination of F Statistics for Multiply Imputed Datasets Using a Chi Square Approximation

Combination of Chi Square Statistics of Multiply Imputed Datasets

Inference for Correlations and Covariances for Multiply Imputed Datasets

Converting a mids, mids.1chain or mids.nmi Object in a Dataset List

Export mids object to MLwiN

MCMC Estimation for Mixed Effects Model

Converting a Nested List into a List (and Vice Versa)

Simulation of Multivariate Linearly Related Non-Normal Variables

R Utilities: Formatting R Output on the R Console

Principal Component Analysis with Ridge Regularization

Pooling for Nested Multiple Imputation

Statistical Inference for Multiply Imputed Datasets

R Utilities: Rounding DIN 1333 (Kaufmaennisches Runden)

R Utilities: Save a Data Frame in Rdata Format

R Utilities: Saving/Writing Data Files using miceadds

Adding a Standardized Variable to a List of Multiply Imputed Datasets or a Single Datasets

R Utilities: Scan a Character Vector

R Utilities: Source all R or Rcpp Files within a Directory

Descriptive Statistics for a Vector or a Data Frame

R Utilities: String Paste Combined with expand.grid

Subsetting Multiply Imputed Datasets and Nested Multiply Imputed Datasets

Sum Preserving Rounding

Synthesizing Method for Fixed Values by Design in synthpop

Synthesizing Method for synthpop Using a Formula Interface

Using a mice Imputation Method in the synthpop Package

Constructs Synthetic Dataset with mice Imputation Methods

R Utilities: Various Strings Representing System Time

Two-Way Imputation

Automatic Determination of a Visit Sequence in mice

Evaluates an Expression for (Nested) Multiply Imputed Datasets

Write a List of Multiply Imputed Datasets

Reading and Writing Files in Fixed Width Format

Export Multiply Imputed Datasets from a mids Object

Writing a Data Frame into SPSS Format Using PSPP Software