Missing Data Imputation and Model Checking

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Documentation for package ‘mi’ version 0.02-02

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

-- B --

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 Virtual class for all mi classes.
coef.mi.mixed Two-stage elementary function: linear regression to impute a variable that can be positive or zero.
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.glm-method Generalized Linear Modeling Function for Multiply Imputed Dataset
display,mi.lm-method Linear Regression Function for Multiply Imputed Dataset

-- F --

fitted.mi.method Virtual class for all mi classes.
fitted.mi.mixed Two-stage elementary function: linear regression to impute a variable that can be positive or zero.

-- G --

glm.mi Generalized Linear Modeling Function 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.method-method Virtual class for all mi classes.
imputed,mi.mixed-method Two-stage elementary function: linear regression to impute a variable that can be positive or zero.
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 Linear Regression Function 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,mi-method Multiple Iterative Regression Imputation
mi-class Multiple Iterative Regression Imputation
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 Dataframe or Matrix
mi.completed,mi-method Multiply Imputed Dataframe or Matrix
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.data.frame Multiply Imputed Dataframe or Matrix
mi.data.frame,mi-method Multiply Imputed Dataframe or Matrix
mi.dichotomous Elementary function: Bayesian logistic regression to impute a dichotomous variable.
mi.dichotomous-class Elementary function: Bayesian logistic regression to impute a dichotomous variable.
mi.fixed Elementary function: imputation of constant variable.
mi.fixed-class Elementary function: imputation of constant variable.
mi.glm-class Generalized Linear Modeling Function for Multiply Imputed Dataset
mi.hist Multiple Imputation Histogram
mi.hist,ANY,ANY-method Multiple Imputation Histogram
mi.hist,ANY-method Multiple Imputation Histogram
mi.hist,mi.categorical,ANY-method Multiple Imputation Histogram
mi.hist,mi.categorical-method Multiple Imputation Histogram
mi.hist,mi.dichotomous,ANY-method Multiple Imputation Histogram
mi.hist,mi.dichotomous-method Multiple Imputation Histogram
mi.hist,mi.method,ANY-method Multiple Imputation Histogram
mi.hist,mi.method-method Multiple Imputation Histogram
mi.hist,mi.mixed,ANY-method Multiple Imputation Histogram
mi.hist,mi.mixed-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.hist,mi.sqrtcontinuous,ANY-method Multiple Imputation Histogram
mi.hist,mi.sqrtcontinuous-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.lm-class Linear Regression Function for Multiply Imputed Dataset
mi.logcontinuous Elementary function: linear regression to impute a continuous positive variable.
mi.logcontinuous-class Elementary function: linear regression to impute a continuous positive variable.
mi.matrix Multiply Imputed Dataframe or Matrix
mi.matrix,mi-method Multiply Imputed Dataframe or Matrix
mi.method Virtual class for all mi classes.
mi.method-class Virtual class for all mi classes.
mi.mixed Two-stage elementary function: linear regression to impute a variable that can be positive or zero.
mi.mixed-class Two-stage elementary function: linear regression to impute a variable that can be positive or zero.
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.scatterplot Multiple Imputation Scatterplot
mi.sqrtcontinuous Elementary function: linear regression to impute a continuous positive variable.
mi.sqrtcontinuous-class Elementary function: linear regression to impute a continuous positive variable.
mi.start Starting value from mi.method objec class.
mi.start,mi.method-method Starting value from mi.method objec class.
mi.start,mi.mixed-method Starting value from mi.method objec class.
mi.types Functions to identify types of the models of the mi object
missing.pattern.plot Missing Pattern Plot
mp.plot Missing Pattern Plot

-- P --

plot.mi Diagnostic Plots for multiple imputation object
plot.mi.categorical Elementary function: multinomial log-linear models to impute a categorical variable.
plot.mi.copy Elementary function: imputation of constant variable.
plot.mi.dichotomous Elementary function: Bayesian logistic regression to impute a dichotomous variable.
plot.mi.logcontinuous Elementary function: linear regression to impute a continuous positive variable.
plot.mi.method Virtual class for all mi classes.
plot.mi.mixed Two-stage elementary function: linear regression to impute a variable that can be positive or zero.
plot.mi.polr Elementary function: multinomial log-linear models to impute a ordered categorical variable.
plot.mi.sqrtcontinuous Elementary function: linear regression to impute a continuous positive variable.
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.mixed-method Two-stage elementary function: linear regression to impute a variable that can be positive or zero.
print.mi.glm Generalized Linear Modeling Function for Multiply Imputed Dataset
print.mi.lm Linear Regression Function for Multiply Imputed Dataset

-- R --

random.imp Random Imputation of Missing Data
residuals.mi.categorical Elementary function: multinomial log-linear models to impute a categorical variable.
residuals.mi.dichotomous Elementary function: Bayesian logistic regression to impute a dichotomous variable.
residuals.mi.logcontinuous Elementary function: linear regression to impute a continuous positive variable.
residuals.mi.method Virtual class for all mi classes.
residuals.mi.mixed Two-stage elementary function: linear regression to impute a variable that can be positive or zero.
residuals.mi.sqrtcontinuous Elementary function: linear regression to impute a continuous positive variable.

-- S --

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.
sigma.hat,mi.mixed-method Two-stage elementary function: linear regression to impute a variable that can be positive or zero.

-- 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