_pkgdown.yml

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
      - 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
      - as.mids
      - as.mira
      - as.mitml.result
      - cbind.mids
      - rbind.mids
      - ibind
      - 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