Compare two nested models using D1-statistic
Compare several nested models
Appends specified break to the data
Complete case indicator
Multivariate Amputation Based On Continuous Probability Functions
Default freq in ampute
Converts an multiply imputed dataset (long format) into a mids object
Extracts the completed data from a mids object
Fluxplot of the missing data pattern
Extract list of fitted model
Create a mira object from repeated analyses
Check for mads object
Check for mids object
Check for mitml.result object
Leiden 85+ study
Imputation by logistic regression using the bootstrap
Construct blocks from formulas and predictorMatrix
Imputation by the mean
Imputation of ordered data by polytomous regression
Density plot of observed and imputed data
Extends a formula with predictors
Imputation of unordered data by polytomous regression
Extends formula's with predictor matrix settings
Creates a formulas argument
Creates a method argument
Export mids object to SPSS
Imputation by a two-level normal model using lmer
Multivariate multilevel imputation using jomo
Imputation by classification and regression trees
Imputation by a two-level normal model
Default odds in ampute()
Imputation by linear regression through prediction
Default patterns in ampute
Impute multilevel missing data using pan
mipo: Multiple imputation pooled object
Imputation of quadratic terms
Brandsma school data used Snijders and Bosker (2012)
Imputation by random forests
Box-and-whisker plot of amputed and non-amputed data
Multiply imputed repeated analyses (mira)
Hox pupil popularity data with missing popularity scores
Project on preterm and small for gestational age infants (POPS)
Employee selection data
Computes least squares parameters
Print a mads object
Name imputation blocks
Extract broken stick estimates from a lmer object
Combine estimates by Rubin's rules
SE Fireworks disaster data
Quick selection of predictors from the data
Multivariate Amputation Based On Discrete Probability Functions
Compare two nested models fitted to imputed data
Potthoff-Roy data
Extract estimate from mipo object
Generalized linear model for mids object
Print a mids object
Compare two nested models using D3-statistic
Terneuzen birth cohort
Creates a blocks argument
Default type in ampute()
Creates a blots argument
Generate Missing Data for Simulation Purposes
Echoes the package version number
Default weights in ampute
Multivariate Amputation In A MCAR Manner
Converts into a mitml.result object
Box-and-whisker plot of observed and imputed data
Growth of Dutch boys
Enlarge number of imputations by combining mids objects
Combine mids objects by columns
Select complete cases
Select incomplete cases
Combine R Objects by Rows and Columns
Fraction of incomplete cases among cases with observed
Fifth Dutch growth study 2009
Fix coefficients and update model
Multivariate Amputed Data Set (mads)
Linear regression for mids object
Influx and outflux of multivariate missing data patterns
Check for mipo object
Creates a visitSequence argument
mice : Multivariate Imputation by Chained Equations
Check for mira object
Imputation by a two-level logistic model using glmer
Missing data pattern
Incomplete case indicator
Graphical parameter for missing data plots.
Conditional imputation helper
Creates a where argument
Creates a post argument
Creates a predictorMatrix argument
Passive imputation
Missing data pattern by variable pairs
Mammal sleep data
Imputation by predictive mean matching
Imputation at level 2 by predictive mean matching
Imputation at level 2 by Bayesian linear regression
Imputation by linear regression, bootstrap method
Imputation by linear discriminant analysis
Imputation by logistic regression
Imputation by a two-level normal model using pan
Multivariate Imputation by Chained Equations (Iteration Step)
Set the theme for the plotting Trellis functions
Number of imputations per block
Imputation of the mean within the class
Export mids object to Mplus
Multiply imputed data set (mids)
Imputation by predictive mean matching with distance aided donor selection
Draws values of beta and sigma by Bayesian linear regression
Plot the trace lines of the MICE algorithm
Name formula list elements
Cumulative hazard rate or Nelson-Aalen estimator
Imputation by linear regression without parameter uncertainty
Imputation by Bayesian linear regression
Imputation by the random indicator method for nonignorable data
Finds an imputed value from matches in the predictive metric (deprecated)
NHANES example - all variables numerical
Summary of a mira object
Multiple imputation pooling: univariate version
Pooling: R squared
Supports semi-transparent foreground colors?
Imputation by simple random sampling
Number of complete cases
NHANES example - mixed numerical and discrete variables
Wrapper function that runs MICE in parallel
Number of incomplete cases
Datasets with various missing data patterns
Combine mids objects by rows
Self-reported and measured BMI
Evaluate an expression in multiple imputed datasets
Scatterplot of observed and imputed data
Scatterplot of amputed and non-amputed data against weighted sum scores
Squeeze the imputed values to be within specified boundaries.
Stripplot of observed and imputed data
Walking disability data
Subset of Irish wind speed data
Compare two nested models using D2-statistic