/
_pkgdown.yml
179 lines (178 loc) · 4.17 KB
/
_pkgdown.yml
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title: mice
url: https://amices.org/mice/
template:
bootstrap: 5
params:
bootswatch: lumen
reference:
- title: Missing data exploration
desc: |
Functions to count and explore the structure of the missing data.
contents:
- md.pattern
- md.pairs
- cc
- cci
- ic
- ici
- mcar
- ncc
- nic
- nimp
- fico
- flux
- fluxplot
- title: Main imputation functions
desc: |
The workflow of multiple imputation is: multiply-impute the data, apply the complete-data model to each imputed data set, and pool the results to get to the final inference. The main functions for imputing the data are:
contents:
- mice
- mice.mids
- parlmice
- futuremice
- title: Elementary imputation functions
desc: |
The elementary imputation function is the workhorse that creates the actual imputations. Elementary functions are called through the `method` argument of `mice` function. Each function imputes one or more columns in the data. There are also `mice.impute.xxx` functions outside the `mice` package.
contents: starts_with("mice.impute")
- title: Imputation model helpers
desc: |
Specification of the imputation models can be made more convenient using the following set of helpers.
contents:
- quickpred
- squeeze
- make.blocks
- make.blots
- make.formulas
- make.method
- make.post
- make.predictorMatrix
- make.visitSequence
- make.where
- construct.blocks
- name.blocks
- name.formulas
- title: Plots comparing observed to imputed/amputed data
desc: |
These plots contrast the observed data with the imputed/amputed data, usually with a blue/red distinction.
contents:
- bwplot.mids
- densityplot.mids
- plot.mids
- stripplot.mids
- xyplot.mids
- title: Repeated analyses and combining analytic estimates
desc: |
Multiple imputation creates m > 1 completed data sets, fits the model of interest to each of these, and combines the analytic estimates. The following functions assist in executing the analysis and pooling steps:
contents:
- with.mids
- pool
- pool.r.squared
- pool.scalar
- pool.table
- nelsonaalen
- pool.compare
- anova.mira
- fix.coef
- D1
- D2
- D3
- title: Data manipulation
desc: |
The multiply-imputed data can be combined in various ways, and exported into other formats.
contents:
- complete
- cbind
- rbind
- ibind
- as.mids
- as.mira
- as.mitml.result
- filter.mids
- mids2mplus
- mids2spss
- title: Class descriptions
desc: |
The data created at the various analytic phases are stored as list objects of a specific class. The most important classes and class-test functions are:
contents:
- mids-class
- mira-class
- is.mids
- is.mipo
- is.mira
- is.mitml.result
- title: Extraction functions
desc: |
Helpers to extract and print information from objects of specific classes.
contents:
- convergence
- getfit
- getqbar
- glance.mipo
- print.mids
- print.mira
- print.mice.anova
- print.mice.anova.summary
- summary.mira
- summary.mids
- summary.mice.anova
- tidy.mipo
- title: Low-level imputation functions
desc: |
Several functions are dedicated to common low-level operations to generate the imputations:
contents:
- estimice
- norm.draw
- .norm.draw
- .pmm.match
- title: Multivariate amputation
desc: |
Amputation is the inverse of imputation, starting with a complete dataset, and creating missing data pattern according to the posited missing data mechanism. Amputation is useful for simulation studies.
contents:
- ampute
- bwplot.mads
- xyplot.mads
- is.mads
- mads-class
- print.mads
- summary.mads
- title: Datasets
desc: Built-in datasets
contents:
- boys
- brandsma
- employee
- fdd
- fdgs
- leiden85
- mammalsleep
- mnar_demo_data
- nhanes
- nhanes2
- pattern
- popmis
- pops
- potthoffroy
- selfreport
- tbc
- toenail
- toenail2
- walking
- windspeed
- title: Miscellaneous functions
desc: Miscellaneous functions
contents:
- appendbreak
- extractBS
- glm.mids
- lm.mids
- matchindex
- mdc
- mice.theme
- supports.transparent
- version
articles:
- title: General
navbar: ~
contents:
- overview
- oldfriends