Man pages for rbmi
Reference Based Multiple Imputation

add_classAdd a class
adjust_trajectoriesAdjust trajectories due to the intercurrent event (ICE)
adjust_trajectories_singleAdjust trajectory of a subject's outcome due to the...
analyseAnalyse Multiple Imputed Datasets
ancovaAnalysis of Covariance
ancova_singleImplements an Analysis of Covariance (ANCOVA)
antidepressant_dataAntidepressant trial data
apply_deltaApplies delta adjustment
as_analysisConstruct an 'analysis' object
as_ascii_tableas_ascii_table
as_classSet Class
as_cropped_charas_cropped_char
as_dataframeConvert object to dataframe
as_drawsCreates a 'draws' object
as_imputationCreate an imputation object
as_indicesConvert indicator to index
as_mmrm_dfCreates a "MMRM" ready dataset
as_mmrm_formulaCreate MMRM formula
as_model_dfExpand 'data.frame' into a design matrix
assert_variables_existAssert that all variables exist within a dataset
as_simple_formulaCreates a simple formula object from a string
as_stan_arrayAs array
as_strataCreate vector of Stratas
char2fctConvert character variables to factor
check_ESSDiagnostics of the MCMC based on ESS
check_hmc_diagnDiagnostics of the MCMC based on HMC-related measures.
check_mcmcDiagnostics of the MCMC
compute_sigmaCompute covariance matrix for some reference-based methods...
convert_to_imputation_list_dfConvert list of 'imputation_list_single()' objects to an...
delta_templateCreate a delta 'data.frame' template
d_lagscaleCalculate delta from a lagged scale coefficient
do_not_runDo not run this function
drawsFit the base imputation model and get parameter estimates
encap_get_mmrm_sampleEncapsulate get_mmrm_sample
eval_mmrmEvaluate a call to mmrm
expandExpand and fill in missing 'data.frame' rows
extract_covariatesExtract Variables from string vector
extract_data_nmar_as_naSet to NA outcome values that would be MNAR if they were...
extract_drawsExtract draws from a 'stanfit' object
extract_imputed_dfExtract imputed dataset
extract_imputed_dfsExtract imputed datasets
extract_paramsExtract parameters from a MMRM model
fit_mcmcFit the base imputation model using a Bayesian approach
fit_mmrmFit a MMRM model
generate_data_singleGenerate data for a single group
get_bootstrap_stackCreates a stack object populated with bootstrapped samples
get_clusterCreate cluster
get_conditional_parametersDerive conditional multivariate normal parameters
get_delta_templateGet delta utility variables
get_draws_mleFit the base imputation model on bootstrap samples
get_ESSExtract the Effective Sample Size (ESS) from a 'stanfit'...
get_ests_bmlmiVon Hippel and Bartlett pooling of BMLMI method
get_example_dataSimulate a realistic example dataset
get_jackknife_stackCreates a stack object populated with jackknife samples
get_mmrm_sampleFit MMRM and returns parameter estimates
get_pattern_groupsDetermine patients missingness group
get_pattern_groups_uniqueGet Pattern Summary
get_pool_componentsExpected Pool Components
getStrategiesGet imputation strategies
get_visit_distribution_parametersDerive visit distribution parameters
has_classDoes object have a class ?
ifeif else
imputation_dfCreate a valid 'imputation_df' object
imputation_list_dfList of imputations_df
imputation_list_singleA collection of 'imputation_singles()' grouped by a single...
imputation_singleCreate a valid 'imputation_single' object
imputeCreate imputed datasets
impute_data_individualImpute data for a single subject
impute_internalCreate imputed datasets
impute_outcomeSample outcome value
invertinvert
invert_indexesInvert and derive indexes
is_absentIs value absent
is_char_factIs character or factor
is_char_oneIs single character
is_in_rbmi_developmentIs package in development mode?
is_num_char_factIs character, factor or numeric
locfLast Observation Carried Forward
longDataConstructorR6 Class for Storing / Accessing & Sampling Longitudinal Data
ls_designCalculate design vector for the lsmeans
lsmeansLeast Square Means
methodSet the multiple imputation methodology
parametric_ciCalculate parametric confidence intervals
poolPool analysis results obtained from the imputed datasets
pool_bootstrap_normalBootstrap Pooling via normal approximation
pool_bootstrap_percentileBootstrap Pooling via Percentiles
pool_internalInternal Pool Methods
prepare_stan_dataPrepare input data to run the Stan model
print.analysisPrint 'analysis' object
print.drawsPrint 'draws' object
print.imputationPrint 'imputation' object
progressLoggerR6 Class for printing current sampling progress
pval_percentileP-value of percentile bootstrap
QR_decompQR decomposition
random_effects_exprConstruct random effects formula
rbmi-packagerbmi: Reference Based Multiple Imputation
recordCapture all Output
recursive_reducerecursive_reduce
remove_if_all_missingRemove subjects from dataset if they have no observed values
rubin_dfBarnard and Rubin degrees of freedom adjustment
rubin_rulesCombine estimates using Rubin's rules
sample_idsSample Patient Ids
sample_listCreate and validate a 'sample_list' object
sample_mvnormSample random values from the multivariate normal...
sample_singleCreate object of 'sample_single' class
scalerConstructorR6 Class for scaling (and un-scaling) design matrices
set_simul_parsSet simulation parameters of a study group.
set_varsSet key variables
simulate_dataGenerate data
simulate_dropoutSimulate drop-out
simulate_iceSimulate intercurrent event
simulate_test_dataCreate simulated datasets
sort_bySort 'data.frame'
split_dimTransform array into list of arrays
split_imputationsSplit a flat list of 'imputation_single()' into multiple...
StackR6 Class for a FIFO stack
strategiesStrategies
str_containsDoes a string contain a substring
string_padstring_pad
transpose_imputationsTranspose imputations
transpose_resultsTranspose results object
transpose_samplesTranspose samples
validateGeneric validation method
validate_analyse_parsValidate analysis results
validate.analysisValidate 'analysis' objects
validate_datalongValidate a longdata object
validate.drawsValidate 'draws' object
validate.is_marValidate 'is_mar' for a given subject
validate.ivarsValidate inputs for 'vars'
validate.referencesValidate user supplied references
validate.sample_listValidate 'sample_list' object
validate.sample_singleValidate 'sample_single' object
validate.simul_parsValidate a 'simul_pars' object
validate.stan_dataValidate a 'stan_data' object
validate_strategiesValidate user specified strategies
rbmi documentation built on Nov. 14, 2022, 5:07 p.m.