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