Missing Data Imputation and Model Checking

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Documentation for package ‘mi’ version 0.08-03

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B C D F G I L M N P R S T U W

-- B --

bayesglm.mi Modeling Functions for Multiply Imputed Dataset
bayespolr.mi Modeling Functions for Multiply Imputed Dataset
bugs.mi Multiple Iterative Regression Imputation
bugs.mi,mi-method Multiple Iterative Regression Imputation

-- C --

call.mi Multiple Iterative Regression Imputation
call.mi,mi-method Multiple Iterative Regression Imputation
CHAIN Subset of variables from the CHAIN project, a longitudinal cohort study of people living with HIV in New York City.
coef,mi.method-method Virtual class for all mi classes.
coef,mi.pooled-method Modeling Functions for Multiply Imputed Dataset
coefficients,mi.method-method Virtual class for all mi classes.
coefficients,mi.pooled-method Modeling Functions for Multiply Imputed Dataset
conv.plot Convergence Plot of mi Object
converged Multiple Iterative Regression Imputation
converged,mi-method Multiple Iterative Regression Imputation
convergence.plot Convergence Plot of mi Object

-- D --

data.mi Multiple Iterative Regression Imputation
data.mi,mi-method Multiple Iterative Regression Imputation
display,mi.pooled-method Modeling Functions for Multiply Imputed Dataset

-- F --

fitted,mi.method-method Virtual class for all mi classes.

-- G --

glm.mi Modeling Functions for Multiply Imputed Dataset
glmer.mi Modeling Functions for Multiply Imputed Dataset

-- I --

imp Multiple Iterative Regression Imputation
imp,mi-method Multiple Iterative Regression Imputation
imp.mi Multiple Iterative Regression Imputation
imp.mi,mi-method Multiple Iterative Regression Imputation
imputed Virtual class for all mi classes.
imputed,mi.categorical-method Virtual class for all mi classes.
imputed,mi.method-method Virtual class for all mi classes.
imputed,mi.polr-method Virtual class for all mi classes.
info.mi Multiple Iterative Regression Imputation
info.mi,mi-method Multiple Iterative Regression Imputation
is.mi Multiple Iterative Regression Imputation
is.mi,mi-method Multiple Iterative Regression Imputation
is.mi.info Function to create information matrix for missing data imputation

-- L --

lm.mi Modeling Functions for Multiply Imputed Dataset
lmer.mi Modeling Functions for Multiply Imputed Dataset

-- M --

m Multiple Iterative Regression Imputation
m,mi-method Multiple Iterative Regression Imputation
marginal.scatterplot Multiple Imputation Scatterplot
mi Multiple Iterative Regression Imputation
mi,data.frame-method Multiple Iterative Regression Imputation
mi,mi-method Multiple Iterative Regression Imputation
mi-class Multiple Iterative Regression Imputation
mi.binary Elementary function: Bayesian logistic regression to impute a binary variable.
mi.binary-class Elementary function: Bayesian logistic regression to impute a binary variable.
mi.categorical Elementary function: multinomial log-linear models to impute a categorical variable.
mi.categorical-class Elementary function: multinomial log-linear models to impute a categorical variable.
mi.completed Multiply Imputed Dataframes
mi.completed,mi-method Multiply Imputed Dataframes
mi.continuous Elementary function: linear regression to impute a continuous variable.
mi.continuous-class Elementary function: linear regression to impute a continuous variable.
mi.copy Elementary function: imputation of constant variable.
mi.copy-class Elementary function: imputation of constant variable.
mi.count Elementary function: Bayesian overdispersed poisson regression to impute a count variable.
mi.count-class Elementary function: Bayesian overdispersed poisson regression to impute a count variable.
mi.data.frame Multiply Imputed Dataframes
mi.data.frame,mi-method Multiply Imputed Dataframes
mi.fixed Elementary function: imputation of constant variable.
mi.fixed-class Elementary function: imputation of constant variable.
mi.hist Multiple Imputation Histogram
mi.hist,ANY,ANY-method Multiple Imputation Histogram
mi.hist,ANY-method Multiple Imputation Histogram
mi.hist,mi.binary,ANY-method Multiple Imputation Histogram
mi.hist,mi.binary-method Multiple Imputation Histogram
mi.hist,mi.categorical,ANY-method Multiple Imputation Histogram
mi.hist,mi.categorical-method Multiple Imputation Histogram
mi.hist,mi.method,ANY-method Multiple Imputation Histogram
mi.hist,mi.method-method Multiple Imputation Histogram
mi.hist,mi.pmm,ANY-method Multiple Imputation Histogram
mi.hist,mi.pmm-method Multiple Imputation Histogram
mi.hist,mi.polr,ANY-method Multiple Imputation Histogram
mi.hist,mi.polr-method Multiple Imputation Histogram
mi.info Function to create information matrix for missing data imputation
mi.info-class Function to create information matrix for missing data imputation
mi.info.fix Function to create information matrix for missing data imputation
mi.info.update function to update mi.info object to use for multiple imputation
mi.info.update.determ.pred function to update mi.info object to use for multiple imputation
mi.info.update.imp.formula function to update mi.info object to use for multiple imputation
mi.info.update.imp.order function to update mi.info object to use for multiple imputation
mi.info.update.include function to update mi.info object to use for multiple imputation
mi.info.update.is.ID function to update mi.info object to use for multiple imputation
mi.info.update.level function to update mi.info object to use for multiple imputation
mi.info.update.other function to update mi.info object to use for multiple imputation
mi.info.update.params function to update mi.info object to use for multiple imputation
mi.info.update.transform function to update mi.info object to use for multiple imputation
mi.info.update.type function to update mi.info object to use for multiple imputation
mi.interactive Function to create information matrix for missing data imputation
mi.method Virtual class for all mi classes.
mi.method-class Virtual class for all mi classes.
mi.pmm Elementary function: Probability Mean Matching for imputation.
mi.pmm-class Elementary function: Probability Mean Matching for imputation.
mi.polr Elementary function: multinomial log-linear models to impute a ordered categorical variable.
mi.polr-class Elementary function: multinomial log-linear models to impute a ordered categorical variable.
mi.pooled Modeling Functions for Multiply Imputed Dataset
mi.pooled-class Modeling Functions for Multiply Imputed Dataset
mi.postprocess Preproessing and Postprocessing mi data object
mi.preprocess Preproessing and Postprocessing mi data object
mi.scatterplot Multiple Imputation Scatterplot
mi.types Functions to identify types of the models of the mi object
missing.pattern.plot Missing Pattern Plot
mp.plot Missing Pattern Plot

-- N --

noise.control Auxiliary for Adding Priors to Missing Data Imputation

-- P --

plot Diagnostic Plots for multiple imputation object
plot,mi,ANY-method Diagnostic Plots for multiple imputation object
plot,mi-method Diagnostic Plots for multiple imputation object
plot,mi.binary,ANY-method Elementary function: Bayesian logistic regression to impute a binary variable.
plot,mi.binary-method Elementary function: Bayesian logistic regression to impute a binary variable.
plot,mi.categorical,ANY-method Elementary function: multinomial log-linear models to impute a categorical variable.
plot,mi.categorical-method Elementary function: multinomial log-linear models to impute a categorical variable.
plot,mi.method,ANY-method Virtual class for all mi classes.
plot,mi.method-method Virtual class for all mi classes.
plot,mi.polr,ANY-method Elementary function: multinomial log-linear models to impute a ordered categorical variable.
plot,mi.polr-method Elementary function: multinomial log-linear models to impute a ordered categorical variable.
plot.mi Diagnostic Plots for multiple imputation object
polr.mi Modeling Functions for Multiply Imputed Dataset
print,mi-method Multiple Iterative Regression Imputation
print,mi.info-method Function to create information matrix for missing data imputation
print,mi.method-method Virtual class for all mi classes.
print.mi.pooled Modeling Functions for Multiply Imputed Dataset

-- R --

random.imp Random Imputation of Missing Data
resid,mi.binary-method Elementary function: Bayesian logistic regression to impute a binary variable.
resid,mi.categorical-method Elementary function: multinomial log-linear models to impute a categorical variable.
resid,mi.count-method Elementary function: Bayesian overdispersed poisson regression to impute a count variable.
resid,mi.method-method Virtual class for all mi classes.
resid,mi.polr-method Elementary function: multinomial log-linear models to impute a ordered categorical variable.
residuals,mi.binary-method Elementary function: Bayesian logistic regression to impute a binary variable.
residuals,mi.categorical-method Elementary function: multinomial log-linear models to impute a categorical variable.
residuals,mi.count-method Elementary function: Bayesian overdispersed poisson regression to impute a count variable.
residuals,mi.method-method Virtual class for all mi classes.
residuals,mi.polr-method Elementary function: multinomial log-linear models to impute a ordered categorical variable.

-- S --

se.coef,mi.pooled-method Modeling Functions for Multiply Imputed Dataset
show,mi-method Multiple Iterative Regression Imputation
show,mi.info-method Function to create information matrix for missing data imputation
sigma.hat,mi.method-method Virtual class for all mi classes.

-- T --

type.models Functions to identify types of the models of the mi object
typecast Variables type
typecast,ANY-method Variables type
typecast,data.frame-method Variables type
typecast,list-method Variables type
typecast,matrix-method Variables type

-- U --

update.mi.info function to update mi.info object to use for multiple imputation

-- W --

write.mi Writes mi impuations to file