Some Additional Multiple Imputation Functions, Especially for 'mice'

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Documentation for package ‘miceadds’ version 3.17-44

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C D F G I J K L M N O P Q R S T V W

miceadds-package Some Additional Multiple Imputation Functions, Especially for 'mice'

-- C --

coef.glm.cluster Cluster Robust Standard Errors for Linear Models and General Linear Models
coef.lm.cluster Cluster Robust Standard Errors for Linear Models and General Linear Models
coef.lmer_vcov Statistical Inference for Fixed and Random Structure for Fitted Models in 'lme4'
coef.mipo.nmi Pooling for Nested Multiple Imputation
coef.ml_mcmc MCMC Estimation for Mixed Effects Model
coef.pool_mi Statistical Inference for Multiply Imputed Datasets
complete.mids.1chain Creates Imputed Dataset from a 'mids.nmi' or 'mids.1chain' Object
complete.mids.nmi Creates Imputed Dataset from a 'mids.nmi' or 'mids.1chain' Object
create.designMatrices.waldtest Wald Test for Nested Multiply Imputed Datasets
crlrem R Utilities: Removing CF Line Endings
cwc Calculation of Groupwise Descriptive Statistics for Matrices
cxxfunction.copy R Utilities: Copy of an 'Rcpp' File

-- D --

data.allison Datasets from Allison's _Missing Data_ Book
data.allison.gssexp Datasets from Allison's _Missing Data_ Book
data.allison.hip Datasets from Allison's _Missing Data_ Book
data.allison.usnews Datasets from Allison's _Missing Data_ Book
data.enders Datasets from Enders' _Missing Data_ Book
data.enders.depression Datasets from Enders' _Missing Data_ Book
data.enders.eatingattitudes Datasets from Enders' _Missing Data_ Book
data.enders.employee Datasets from Enders' _Missing Data_ Book
data.graham Datasets from Grahams _Missing Data_ Book
data.graham.ex3 Datasets from Grahams _Missing Data_ Book
data.graham.ex6 Datasets from Grahams _Missing Data_ Book
data.graham.ex8a Datasets from Grahams _Missing Data_ Book
data.graham.ex8b Datasets from Grahams _Missing Data_ Book
data.graham.ex8c Datasets from Grahams _Missing Data_ Book
data.internet Dataset Internet
data.largescale Large-scale Dataset for Testing Purposes (Many Cases, Few Variables)
data.ma Example Datasets for 'miceadds' Package
data.ma01 Example Datasets for 'miceadds' Package
data.ma02 Example Datasets for 'miceadds' Package
data.ma03 Example Datasets for 'miceadds' Package
data.ma04 Example Datasets for 'miceadds' Package
data.ma05 Example Datasets for 'miceadds' Package
data.ma06 Example Datasets for 'miceadds' Package
data.ma07 Example Datasets for 'miceadds' Package
data.ma08 Example Datasets for 'miceadds' Package
data.ma09 Example Datasets for 'miceadds' Package
data.smallscale Small-Scale Dataset for Testing Purposes (Moderate Number of Cases, Many Variables)
datalist2mids Converting a List of Multiply Imputed Data Sets into a 'mids' Object
datlist2Amelia Converting an Object of class 'amelia'
datlist2mids Converting a List of Multiply Imputed Data Sets into a 'mids' Object
datlist2nested.datlist Creates Objects of Class 'datlist' or 'nested.datlist'
datlist_create Creates Objects of Class 'datlist' or 'nested.datlist'
draw.pv.ctt Plausible Value Imputation Using a Known Measurement Error Variance (Based on Classical Test Theory)

-- F --

fast.groupmean Defunct 'miceadds' Functions
fast.groupsum Defunct 'miceadds' Functions
filename_split Some Functionality for Strings and File Names
filename_split_vec Some Functionality for Strings and File Names
files_move Moves Files from One Directory to Another Directory
fleishman_coef Simulating Univariate Data from Fleishman Power Normal Transformations
fleishman_sim Simulating Univariate Data from Fleishman Power Normal Transformations

-- G --

glm.cluster Cluster Robust Standard Errors for Linear Models and General Linear Models
gm Calculation of Groupwise Descriptive Statistics for Matrices
grep.vec R Utilities: Vector Based Versions of 'grep'
grepvec R Utilities: Vector Based Versions of 'grep'
grepvec_leading R Utilities: Vector Based Versions of 'grep'
grep_leading R Utilities: Vector Based Versions of 'grep'
GroupMean Calculation of Groupwise Descriptive Statistics for Matrices
GroupSD Calculation of Groupwise Descriptive Statistics for Matrices
GroupSum Calculation of Groupwise Descriptive Statistics for Matrices

-- I --

index.dataframe R Utilities: Include an Index to a Data Frame
in_CI Indicator Function for Analyzing Coverage

-- J --

jomo2datlist Converts a 'jomo' Data Frame in Long Format into a List of Datasets or an Object of Class 'mids'
jomo2mids Converts a 'jomo' Data Frame in Long Format into a List of Datasets or an Object of Class 'mids'

-- K --

kernelpls.fit2 Kernel PLS Regression

-- L --

library_install R Utilities: Loading a Package or Installation of a Package if Necessary
List2nestedList Converting a Nested List into a List (and Vice Versa)
lm.cluster Cluster Robust Standard Errors for Linear Models and General Linear Models
lmer_pool Statistical Inference for Fixed and Random Structure for Fitted Models in 'lme4'
lmer_pool2 Statistical Inference for Fixed and Random Structure for Fitted Models in 'lme4'
lmer_vcov Statistical Inference for Fixed and Random Structure for Fitted Models in 'lme4'
lmer_vcov2 Statistical Inference for Fixed and Random Structure for Fitted Models in 'lme4'
load.data R Utilities: Loading/Reading Data Files using 'miceadds'
load.files R Utilities: Loading/Reading Data Files using 'miceadds'
load.Rdata R Utilities: Loading 'Rdata' Files in a Convenient Way
load.Rdata2 R Utilities: Loading 'Rdata' Files in a Convenient Way

-- M --

ma.scale2 Standardization of a Matrix
ma.wtd.corNA Some Multivariate Descriptive Statistics for Weighted Data in 'miceadds'
ma.wtd.covNA Some Multivariate Descriptive Statistics for Weighted Data in 'miceadds'
ma.wtd.kurtosisNA Some Multivariate Descriptive Statistics for Weighted Data in 'miceadds'
ma.wtd.meanNA Some Multivariate Descriptive Statistics for Weighted Data in 'miceadds'
ma.wtd.quantileNA Some Multivariate Descriptive Statistics for Weighted Data in 'miceadds'
ma.wtd.sdNA Some Multivariate Descriptive Statistics for Weighted Data in 'miceadds'
ma.wtd.skewnessNA Some Multivariate Descriptive Statistics for Weighted Data in 'miceadds'
ma.wtd.statNA Some Multivariate Descriptive Statistics for Weighted Data in 'miceadds'
max0 Descriptive Statistics for a Vector or a Data Frame
ma_exists Utility Functions in 'miceadds'
ma_exists_get Utility Functions in 'miceadds'
ma_lme4_formula Utility Functions for Working with 'lme4' Formula Objects
ma_lme4_formula_design_matrices Utility Functions for Working with 'lme4' Formula Objects
ma_lme4_formula_terms Utility Functions for Working with 'lme4' Formula Objects
ma_rmvnorm Simulating Normally Distributed Data
mean0 Descriptive Statistics for a Vector or a Data Frame
mi.anova Analysis of Variance for Multiply Imputed Data Sets (Using the D_2 Statistic)
mice.1chain Multiple Imputation by Chained Equations using One Chain
mice.impute.2l.binary Imputation of a Continuous or a Binary Variable From a Two-Level Regression Model using 'lme4' or 'blme'
mice.impute.2l.contextual.norm Imputation by Predictive Mean Matching or Normal Linear Regression with Contextual Variables
mice.impute.2l.contextual.pmm Imputation by Predictive Mean Matching or Normal Linear Regression with Contextual Variables
mice.impute.2l.continuous Imputation of a Continuous or a Binary Variable From a Two-Level Regression Model using 'lme4' or 'blme'
mice.impute.2l.groupmean Imputation of Latent and Manifest Group Means for Multilevel Data
mice.impute.2l.groupmean.elim Imputation of Latent and Manifest Group Means for Multilevel Data
mice.impute.2l.latentgroupmean.mcmc Imputation of Latent and Manifest Group Means for Multilevel Data
mice.impute.2l.latentgroupmean.ml Imputation of Latent and Manifest Group Means for Multilevel Data
mice.impute.2l.plausible.values Defunct 'miceadds' Functions
mice.impute.2l.pls Defunct 'miceadds' Functions
mice.impute.2l.pls2 Imputation using Partial Least Squares for Dimension Reduction
mice.impute.2l.pmm Imputation of a Continuous or a Binary Variable From a Two-Level Regression Model using 'lme4' or 'blme'
mice.impute.2lonly.function Imputation at Level 2 (in 'miceadds')
mice.impute.2lonly.norm2 Defunct 'miceadds' Functions
mice.impute.2lonly.pmm2 Defunct 'miceadds' Functions
mice.impute.bygroup Groupwise Imputation Function
mice.impute.catpmm Imputation of a Categorical Variable Using Multivariate Predictive Mean Matching
mice.impute.constant Imputation Using a Fixed Vector
mice.impute.hotDeck Imputation of a Variable Using Probabilistic Hot Deck Imputation
mice.impute.imputeR.cFun Wrapper Function to Imputation Methods in the 'imputeR' Package
mice.impute.imputeR.lmFun Wrapper Function to Imputation Methods in the 'imputeR' Package
mice.impute.lm Imputation of a Linear Model by Bayesian Bootstrap
mice.impute.lm_fun Imputation of a Linear Model by Bayesian Bootstrap
mice.impute.lqs Imputation of a Linear Model by Bayesian Bootstrap
mice.impute.ml.lmer Multilevel Imputation Using 'lme4'
mice.impute.plausible.values Plausible Value Imputation using Classical Test Theory and Based on Individual Likelihood
mice.impute.pls Imputation using Partial Least Squares for Dimension Reduction
mice.impute.pmm3 Imputation by Predictive Mean Matching (in 'miceadds')
mice.impute.pmm4 Imputation by Predictive Mean Matching (in 'miceadds')
mice.impute.pmm5 Imputation by Predictive Mean Matching (in 'miceadds')
mice.impute.pmm6 Imputation by Predictive Mean Matching (in 'miceadds')
mice.impute.rlm Imputation of a Linear Model by Bayesian Bootstrap
mice.impute.simputation Wrapper Function to Imputation Methods in the 'simputation' Package
mice.impute.smcfcs Substantive Model Compatible Multiple Imputation (Single Level)
mice.impute.synthpop Using a 'synthpop' Synthesizing Method in the 'mice' Package
mice.impute.tricube.pmm Imputation by Tricube Predictive Mean Matching
mice.impute.tricube.pmm2 Defunct 'miceadds' Functions
mice.impute.weighted.norm Imputation by Weighted Predictive Mean Matching or Weighted Normal Linear Regression
mice.impute.weighted.pmm Imputation by Weighted Predictive Mean Matching or Weighted Normal Linear Regression
mice.nmi Nested Multiple Imputation
miceadds Some Additional Multiple Imputation Functions, Especially for 'mice'
miceadds-defunct Defunct 'miceadds' Functions
miceadds-utilities Utility Functions in 'miceadds'
miceadds_rcpp_ml_mcmc_compute_xtx MCMC Estimation for Mixed Effects Model
miceadds_rcpp_ml_mcmc_compute_ztz MCMC Estimation for Mixed Effects Model
miceadds_rcpp_ml_mcmc_predict_fixed MCMC Estimation for Mixed Effects Model
miceadds_rcpp_ml_mcmc_predict_fixed_random MCMC Estimation for Mixed Effects Model
miceadds_rcpp_ml_mcmc_predict_random MCMC Estimation for Mixed Effects Model
miceadds_rcpp_ml_mcmc_predict_random_list MCMC Estimation for Mixed Effects Model
miceadds_rcpp_ml_mcmc_probit_category_prob MCMC Estimation for Mixed Effects Model
miceadds_rcpp_ml_mcmc_sample_beta MCMC Estimation for Mixed Effects Model
miceadds_rcpp_ml_mcmc_sample_latent_probit MCMC Estimation for Mixed Effects Model
miceadds_rcpp_ml_mcmc_sample_psi MCMC Estimation for Mixed Effects Model
miceadds_rcpp_ml_mcmc_sample_sigma2 MCMC Estimation for Mixed Effects Model
miceadds_rcpp_ml_mcmc_sample_thresholds MCMC Estimation for Mixed Effects Model
miceadds_rcpp_ml_mcmc_sample_u MCMC Estimation for Mixed Effects Model
miceadds_rcpp_ml_mcmc_subtract_fixed MCMC Estimation for Mixed Effects Model
miceadds_rcpp_ml_mcmc_subtract_random MCMC Estimation for Mixed Effects Model
miceadds_rcpp_pnorm MCMC Estimation for Mixed Effects Model
miceadds_rcpp_qnorm MCMC Estimation for Mixed Effects Model
miceadds_rcpp_rtnorm MCMC Estimation for Mixed Effects Model
mice_imputation_get_states Utility Functions in 'miceadds'
mice_inits Arguments for 'mice::mice' Function
micombine.chisquare Combination of Chi Square Statistics of Multiply Imputed Datasets
micombine.cor Inference for Correlations and Covariances for Multiply Imputed Datasets
micombine.cov Inference for Correlations and Covariances for Multiply Imputed Datasets
micombine.F Combination of F Statistics for Multiply Imputed Datasets Using a Chi Square Approximation
MIcombine.NestedImputationResultList Functions for Analysis of Nested Multiply Imputed Datasets
mids2datlist Converting a 'mids', 'mids.1chain' or 'mids.nmi' Object in a Dataset List
mids2mlwin Export 'mids' object to MLwiN
min0 Descriptive Statistics for a Vector or a Data Frame
MIwaldtest Wald Test for Nested Multiply Imputed Datasets
mi_dstat Cohen's d Effect Size for Missingness Indicators
ml_mcmc MCMC Estimation for Mixed Effects Model
ml_mcmc_fit MCMC Estimation for Mixed Effects Model

-- N --

nested.datlist2datlist Creates Objects of Class 'datlist' or 'nested.datlist'
nested.datlist_create Creates Objects of Class 'datlist' or 'nested.datlist'
NestedImputationList Functions for Analysis of Nested Multiply Imputed Datasets
nestedList2List Converting a Nested List into a List (and Vice Versa)
NMIcombine Pooling for Nested Multiple Imputation
NMIextract Pooling for Nested Multiple Imputation
NMIwaldtest Wald Test for Nested Multiply Imputed Datasets
nnig_coef Simulation of Multivariate Linearly Related Non-Normal Variables
nnig_sim Simulation of Multivariate Linearly Related Non-Normal Variables

-- O --

output.format1 R Utilities: Formatting R Output on the R Console

-- P --

pca.covridge Principal Component Analysis with Ridge Regularization
plot.mids.1chain Multiple Imputation by Chained Equations using One Chain
plot.ml_mcmc MCMC Estimation for Mixed Effects Model
pool.mids.nmi Pooling for Nested Multiple Imputation
pool_mi Statistical Inference for Multiply Imputed Datasets
pool_nmi Pooling for Nested Multiple Imputation
predict.kernelpls.fit2 Kernel PLS Regression
print.datlist Creates Objects of Class 'datlist' or 'nested.datlist'
print.mids.1chain Multiple Imputation by Chained Equations using One Chain
print.mids.nmi Nested Multiple Imputation
print.nested.datlist Creates Objects of Class 'datlist' or 'nested.datlist'
print.NestedImputationList Functions for Analysis of Nested Multiply Imputed Datasets
prop_miss Descriptive Statistics for a Vector or a Data Frame

-- Q --

quantile0 Descriptive Statistics for a Vector or a Data Frame

-- R --

Rcppfunction Utility Functions for Writing R Functions
Rcppfunction_remove_classes Utility Functions for Writing R Functions
rcpp_create_header_file R Utilities: Source all R or 'Rcpp' Files within a Directory
read.fwf2 Reading and Writing Files in Fixed Width Format
Reval R Utilities: Evaluates a String as an Expression in R
Revalpr R Utilities: Evaluates a String as an Expression in R
Revalprstr R Utilities: Evaluates a String as an Expression in R
Revalpr_maxabs R Utilities: Evaluates a String as an Expression in R
Revalpr_round R Utilities: Evaluates a String as an Expression in R
Rfunction Utility Functions for Writing R Functions
Rfunction_include_argument_values Utility Functions for Writing R Functions
Rfunction_output_list_result_function Utility Functions for Writing R Functions
Rhat.mice Rhat Convergence Statistic of a 'mice' Imputation
round2 R Utilities: Rounding DIN 1333 (Kaufmaennisches Runden)
Rsessinfo R Utilities: R Session Information

-- S --

save.data R Utilities: Saving/Writing Data Files using 'miceadds'
save.Rdata R Utilities: Save a Data Frame in 'Rdata' Format
scale_datlist Adding a Standardized Variable to a List of Multiply Imputed Datasets or a Single Datasets
scan.vec R Utilities: Scan a Character Vector
scan.vector R Utilities: Scan a Character Vector
scan0 R Utilities: Scan a Character Vector
sd0 Descriptive Statistics for a Vector or a Data Frame
source.all R Utilities: Source all R or 'Rcpp' Files within a Directory
source.Rcpp.all R Utilities: Source all R or 'Rcpp' Files within a Directory
stats0 Descriptive Statistics for a Vector or a Data Frame
string_extract_part Some Functionality for Strings and File Names
string_to_matrix Some Functionality for Strings and File Names
str_C.expand.grid R Utilities: String Paste Combined with 'expand.grid'
subset.datlist Subsetting Multiply Imputed Datasets and Nested Multiply Imputed Datasets
subset.imputationList Subsetting Multiply Imputed Datasets and Nested Multiply Imputed Datasets
subset.mids Subsetting Multiply Imputed Datasets and Nested Multiply Imputed Datasets
subset.mids.1chain Subsetting Multiply Imputed Datasets and Nested Multiply Imputed Datasets
subset.nested.datlist Subsetting Multiply Imputed Datasets and Nested Multiply Imputed Datasets
subset.NestedImputationList Subsetting Multiply Imputed Datasets and Nested Multiply Imputed Datasets
subset_datlist Subsetting Multiply Imputed Datasets and Nested Multiply Imputed Datasets
subset_nested.datlist Subsetting Multiply Imputed Datasets and Nested Multiply Imputed Datasets
summary.glm.cluster Cluster Robust Standard Errors for Linear Models and General Linear Models
summary.lm.cluster Cluster Robust Standard Errors for Linear Models and General Linear Models
summary.lmer_pool Statistical Inference for Fixed and Random Structure for Fitted Models in 'lme4'
summary.lmer_vcov Statistical Inference for Fixed and Random Structure for Fitted Models in 'lme4'
summary.mids.1chain Multiple Imputation by Chained Equations using One Chain
summary.mids.nmi Nested Multiple Imputation
summary.mipo.nmi Pooling for Nested Multiple Imputation
summary.mira.nmi Evaluates an Expression for (Nested) Multiply Imputed Datasets
summary.MIwaldtest Wald Test for Nested Multiply Imputed Datasets
summary.ml_mcmc MCMC Estimation for Mixed Effects Model
summary.NMIwaldtest Wald Test for Nested Multiply Imputed Datasets
summary.pool_mi Statistical Inference for Multiply Imputed Datasets
sumpreserving.rounding Sum Preserving Rounding
syn.constant Synthesizing Method for Fixed Values by Design in 'synthpop'
syn.formula Synthesizing Method for 'synthpop' Using a Formula Interface
syn.mice Using a 'mice' Imputation Method in the 'synthpop' Package
syn_da Generation of Synthetic Data Utilizing Data Augmentation
syn_mice Constructs Synthetic Dataset with 'mice' Imputation Methods
systime R Utilities: Various Strings Representing System Time

-- T --

tw.imputation Two-Way Imputation
tw.mcmc.imputation Two-Way Imputation

-- V --

var0 Descriptive Statistics for a Vector or a Data Frame
VariableNames2String Stringing Variable Names with Line Breaks
vcov.glm.cluster Cluster Robust Standard Errors for Linear Models and General Linear Models
vcov.lm.cluster Cluster Robust Standard Errors for Linear Models and General Linear Models
vcov.lmer_vcov Statistical Inference for Fixed and Random Structure for Fitted Models in 'lme4'
vcov.mipo.nmi Pooling for Nested Multiple Imputation
vcov.ml_mcmc MCMC Estimation for Mixed Effects Model
vcov.pool_mi Statistical Inference for Multiply Imputed Datasets
visitSequence.determine Automatic Determination of a Visit Sequence in 'mice'

-- W --

with.datlist Evaluates an Expression for (Nested) Multiply Imputed Datasets
with.mids.1chain Evaluates an Expression for (Nested) Multiply Imputed Datasets
with.mids.nmi Evaluates an Expression for (Nested) Multiply Imputed Datasets
with.nested.datlist Evaluates an Expression for (Nested) Multiply Imputed Datasets
with.NestedImputationList Evaluates an Expression for (Nested) Multiply Imputed Datasets
within.datlist Evaluates an Expression for (Nested) Multiply Imputed Datasets
within.imputationList Evaluates an Expression for (Nested) Multiply Imputed Datasets
within.nested.datlist Evaluates an Expression for (Nested) Multiply Imputed Datasets
within.NestedImputationList Evaluates an Expression for (Nested) Multiply Imputed Datasets
withPool_MI Evaluates an Expression for (Nested) Multiply Imputed Datasets
withPool_NMI Evaluates an Expression for (Nested) Multiply Imputed Datasets
write.datlist Write a List of Multiply Imputed Datasets
write.fwf2 Reading and Writing Files in Fixed Width Format
write.mice.imputation Export Multiply Imputed Datasets from a 'mids' Object
write.pspp Writing a Data Frame into SPSS Format Using PSPP Software