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