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rbmi  

Reference Based Multiple Imputation
View on CRAN: Click here


Download and install rbmi package within the R console
Install from CRAN:
install.packages("rbmi")

Install from Github:
library("remotes")
install_github("cran/rbmi")

Install by package version:
library("remotes")
install_version("rbmi", "1.3.1")



Attach the package and use:
library("rbmi")
Maintained by
Craig Gower-Page
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2022-03-03
Latest Update: 2023-11-24
Description:
Implements standard and reference based multiple imputation methods for continuous longitudinal endpoints (Gower-Page et al. (2022) ). In particular, this package supports deterministic conditional mean imputation and jackknifing as described in Wolbers et al. (2022) , Bayesian multiple imputation as described in Carpenter et al. (2013) , and bootstrapped maximum likelihood imputation as described in von Hippel and Bartlett (2021) .
How to cite:
Craig Gower-Page (2022). rbmi: Reference Based Multiple Imputation. R package version 1.3.1, https://cran.r-project.org/web/packages/rbmi. Accessed 03 Feb. 2025.
Previous versions and publish date:
1.1.0 (2022-03-03 01:00), 1.1.1 (2022-03-08 14:10), 1.1.3 (2022-03-21 16:50), 1.1.4 (2022-05-18 18:30), 1.2.1 (2022-10-25 22:42), 1.2.3 (2022-11-14 10:20), 1.2.5 (2023-09-21 01:20), 1.2.6 (2023-11-24 15:00), 1.3.0 (2024-10-16 17:10)
Other packages that cited rbmi R package
View rbmi citation profile
Other R packages that rbmi depends, imports, suggests or enhances
Complete documentation for rbmi
Functions, R codes and Examples using the rbmi R package
Some associated functions: QR_decomp . Stack . add_class . adjust_trajectories . adjust_trajectories_single . analyse . ancova . ancova_single . antidepressant_data . apply_delta . as_analysis . as_ascii_table . as_class . as_cropped_char . as_dataframe . as_draws . as_imputation . as_indices . as_mmrm_df . as_mmrm_formula . as_model_df . as_simple_formula . as_stan_array . as_strata . assert_variables_exist . char2fct . check_ESS . check_hmc_diagn . check_mcmc . compute_sigma . convert_to_imputation_list_df . d_lagscale . delta_template . do_not_run . draws . encap_get_mmrm_sample . eval_mmrm . expand . extract_covariates . extract_data_nmar_as_na . extract_draws . extract_imputed_df . extract_imputed_dfs . extract_params . fit_mcmc . fit_mmrm . generate_data_single . getStrategies . get_ESS . get_bootstrap_stack . get_cluster . get_conditional_parameters . get_delta_template . get_draws_mle . get_ests_bmlmi . get_example_data . get_jackknife_stack . get_mmrm_sample . get_pattern_groups . get_pattern_groups_unique . get_pool_components . get_visit_distribution_parameters . has_class . ife . imputation_df . imputation_list_df . imputation_list_single . imputation_single . impute . impute_data_individual . impute_internal . impute_outcome . invert . invert_indexes . is_absent . is_char_fact . is_char_one . is_in_rbmi_development . is_num_char_fact . locf . longDataConstructor . ls_design . lsmeans . method . parametric_ci . pool . pool_bootstrap_normal . pool_bootstrap_percentile . pool_internal . prepare_stan_data . print.analysis . print.draws . print.imputation . progressLogger . pval_percentile . random_effects_expr . rbmi-package . record . recursive_reduce . remove_if_all_missing . rubin_df . rubin_rules . sample_ids . sample_list . sample_mvnorm . sample_single . scalerConstructor . set_simul_pars . set_vars . simulate_data . simulate_dropout . simulate_ice . simulate_test_data . sort_by . split_dim . split_imputations . str_contains . strategies . string_pad . transpose_imputations . transpose_results . transpose_samples . validate.analysis . validate.draws . validate.is_mar . validate.ivars . validate . validate.references . validate.sample_list . validate.sample_single . validate.simul_pars . validate.stan_data . validate_analyse_pars . validate_datalong . validate_strategies . 
Some associated R codes: analyse.R . ancova.R . as_ascii_table.R . bootstrap.R . data.R . dataclasses.R . delta.R . draws.R . expand.R . impute.R . longData.R . lsmeans.R . mcmc.R . methods.R . mmrm.R . parallel.R . pool.R . rbmi.R . scaling.R . simulate.R . simulate_data.R . stack.R . stanmodels.R . strategies.R . utilities.R . validate.R . validate_datalong.R .  Full rbmi package functions and examples
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