| 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.
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| coef,mi.glm-method |
Generalized Linear Modeling Function for Multiply Imputed Dataset |
| coef,mi.lm-method |
Linear Regression Function for Multiply Imputed Dataset |
| coef,mi.mer-method |
Fit A Linear Mixed Model or A Generalized Linear Mixed Model for Multiply Imputed Dataset |
| coef,mi.method-method |
Virtual class for all mi classes.
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| coefficients,mi.glm-method |
Generalized Linear Modeling Function for Multiply Imputed Dataset |
| coefficients,mi.lm-method |
Linear Regression Function for Multiply Imputed Dataset |
| coefficients,mi.mer-method |
Fit A Linear Mixed Model or A Generalized Linear Mixed Model for Multiply Imputed Dataset |
| coefficients,mi.method-method |
Virtual class for all mi classes.
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| 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 |
| 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.categorical |
Elementary function: multinomial log-linear models to impute a categorical variable.
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| mi.categorical-class |
Elementary function: multinomial log-linear models to impute a categorical variable.
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| mi.completed |
Multiple Imputed Dataframes
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| mi.completed,mi-method |
Multiple Imputed Dataframes
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| mi.continuous |
Elementary function: linear regression to impute a continuous variable.
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| mi.continuous-class |
Elementary function: linear regression to impute a continuous variable.
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| mi.copy |
Elementary function: imputation of constant variable.
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| mi.copy-class |
Elementary function: imputation of constant variable.
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| mi.count |
Elementary function: Bayesian overdispersed poisson regression to impute a count variable.
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| mi.count-class |
Elementary function: Bayesian overdispersed poisson regression to impute a count variable.
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| mi.data.frame |
Multiple Imputed Dataframes
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| mi.data.frame,mi-method |
Multiple Imputed Dataframes
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| mi.dichotomous |
Elementary function: Bayesian logistic regression to impute a dichotomous variable.
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| mi.dichotomous-class |
Elementary function: Bayesian logistic regression to impute a dichotomous variable.
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| mi.fixed |
Elementary function: imputation of constant variable.
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| mi.fixed-class |
Elementary function: imputation of constant variable.
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| mi.glm-class |
Generalized Linear Modeling Function for Multiply Imputed Dataset |
| mi.hist |
Multiple Imputation Histogram
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| mi.hist,ANY,ANY-method |
Multiple Imputation Histogram
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| mi.hist,ANY-method |
Multiple Imputation Histogram
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| mi.hist,mi.categorical,ANY-method |
Multiple Imputation Histogram
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| mi.hist,mi.categorical-method |
Multiple Imputation Histogram
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| mi.hist,mi.dichotomous,ANY-method |
Multiple Imputation Histogram
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| mi.hist,mi.dichotomous-method |
Multiple Imputation Histogram
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| mi.hist,mi.method,ANY-method |
Multiple Imputation Histogram
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| mi.hist,mi.method-method |
Multiple Imputation Histogram
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| mi.hist,mi.pmm,ANY-method |
Multiple Imputation Histogram
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| mi.hist,mi.pmm-method |
Multiple Imputation Histogram
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| mi.hist,mi.polr,ANY-method |
Multiple Imputation Histogram
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| mi.hist,mi.polr-method |
Multiple Imputation Histogram
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| 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.mer-class |
Fit A Linear Mixed Model or A Generalized Linear Mixed Model for Multiply Imputed Dataset |
| mi.method |
Virtual class for all mi classes.
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| mi.method-class |
Virtual class for all mi classes.
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| mi.pmm |
Elementary function: Probability Mean Matching for imputation.
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| mi.pmm-class |
Elementary function: Probability Mean Matching for imputation.
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| mi.polr |
Elementary function: multinomial log-linear models to impute a ordered categorical variable.
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| mi.polr-class |
Elementary function: multinomial log-linear models to impute a ordered categorical variable.
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| 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,missing-method |
Diagnostic Plots for multiple imputation object |
| plot,mi.categorical,ANY-method |
Elementary function: multinomial log-linear models to impute a categorical variable.
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| plot,mi.dichotomous,ANY-method |
Elementary function: Bayesian logistic regression to impute a dichotomous variable.
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| plot,mi.method,ANY-method |
Virtual class for all mi classes.
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| plot,mi.polr,ANY-method |
Elementary function: multinomial log-linear models to impute a ordered categorical variable.
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| plot.mi |
Diagnostic Plots for multiple imputation object |
| 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.
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| print.mi.glm |
Generalized Linear Modeling Function for Multiply Imputed Dataset |
| print.mi.lm |
Linear Regression Function for Multiply Imputed Dataset |
| print.mi.mer |
Fit A Linear Mixed Model or A Generalized Linear Mixed Model for Multiply Imputed Dataset |
| prior.control |
Auxiliary for Adding Priors to Missing Data Imputation |
| random.imp |
Random Imputation of Missing Data |
| resid,mi.categorical-method |
Elementary function: multinomial log-linear models to impute a categorical variable.
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| resid,mi.count-method |
Elementary function: Bayesian overdispersed poisson regression to impute a count variable.
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| resid,mi.dichotomous-method |
Elementary function: Bayesian logistic regression to impute a dichotomous variable.
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| resid,mi.method-method |
Virtual class for all mi classes.
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| resid,mi.polr-method |
Elementary function: multinomial log-linear models to impute a ordered categorical variable.
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| residuals,mi.categorical-method |
Elementary function: multinomial log-linear models to impute a categorical variable.
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| residuals,mi.count-method |
Elementary function: Bayesian overdispersed poisson regression to impute a count variable.
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| residuals,mi.dichotomous-method |
Elementary function: Bayesian logistic regression to impute a dichotomous variable.
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| residuals,mi.method-method |
Virtual class for all mi classes.
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| residuals,mi.polr-method |
Elementary function: multinomial log-linear models to impute a ordered categorical variable.
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