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 |
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 |
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. |