Other packages > Find by keyword >

mdmb  

Model Based Treatment of Missing Data
View on CRAN: Click here


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

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

Install by package version:
library("remotes")
install_version("mdmb", "1.9-22")



Attach the package and use:
library("mdmb")
Maintained by
Alexander Robitzsch
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2017-01-26
Latest Update: 2023-02-28
Description:
Contains model-based treatment of missing data for regression models with missing values in covariates or the dependent variable using maximum likelihood or Bayesian estimation (Ibrahim et al., 2005; ; Luedtke, Robitzsch, & West, 2020a, 2020b; ). The regression model can be nonlinear (e.g., interaction effects, quadratic effects or B-spline functions). Multilevel models with missing data in predictors are available for Bayesian estimation. Substantive-model compatible multiple imputation can be also conducted.
How to cite:
Alexander Robitzsch (2017). mdmb: Model Based Treatment of Missing Data. R package version 1.9-22, https://cran.r-project.org/web/packages/mdmb. Accessed 30 Jan. 2025.
Previous versions and publish date:
0.1-0 (2017-01-26 12:08), 0.2-0 (2017-02-07 16:23), 0.3-11 (2017-07-12 21:14), 0.4-15 (2017-08-20 14:40), 0.5-27 (2018-01-22 11:47), 0.6-17 (2018-02-16 12:10), 0.7-19 (2018-04-24 19:20), 0.8-47 (2018-07-09 19:10), 0.9-43 (2018-08-08 16:30), 0.10-13 (2018-09-12 14:40), 0.11-7 (2018-10-16 21:10), 1.0-18 (2018-11-06 19:10), 1.1-51 (2019-01-07 18:50), 1.2-4 (2019-01-11 13:20), 1.3-18 (2019-04-16 13:53), 1.4-12 (2020-05-12 19:11), 1.5-8 (2021-01-21 16:10), 1.6-5 (2022-05-17 16:00), 1.7-22 (2023-02-17 16:10), 1.8-7 (2023-02-28 23:02)
Other packages that cited mdmb R package
View mdmb citation profile
Other R packages that mdmb depends, imports, suggests or enhances
Complete documentation for mdmb
Functions, R codes and Examples using the mdmb R package
Some associated functions: data.mb . eval_prior_list . frm . mdmb-package . mdmb_regression . offset_values_extract . oprobit_dist . remove_NA_data_frame . yjt_dist . 
Some associated R codes: RcppExports.R . bc_antitrafo.R . bc_trafo.R . bc_trafo_derivative.R . bct_regression.R . coef.mdmb.R . dbct_scaled.R . dbct_scaled_mdmb_regression_wrapper.R . doprobit.R . dt_scaled.R . dyjt_scaled.R . dyjt_scaled_log_multiplication.R . eval_prior_list.R . eval_prior_list_gradient_log.R . eval_prior_list_sumlog.R . fit_bct_scaled.R . fit_mdmb_distribution.R . fit_mdmb_distribution_extract_results.R . fit_mdmb_distribution_logLik_extract.R . fit_mdmb_distribution_remove_NA.R . fit_mdmb_distribution_summary.R . fit_mdmb_distribution_summary_table.R . fit_oprobit.R . fit_t_scaled.R . fit_yjt_scaled.R . frm2datlist.R . frm_append_list.R . frm_check_predictor_matrix.R . frm_define_model_R_function.R . frm_define_model_R_function_include_maxiter.R . frm_descriptives_variables.R . frm_em.R . frm_em_avcov.R . frm_em_calc_likelihood.R . frm_em_calc_likelihood_estimate_model.R . frm_em_calc_total_likelihood.R . frm_em_calc_update_observed_likelihood.R . frm_em_ic.R . frm_em_include_coef_inits.R . frm_em_linreg_density_extend_args.R . frm_em_score_function_prepare_model.R . frm_em_summary_print_nodes.R . frm_estimate_model_create_R_args.R . frm_fb.R . frm_fb_descriptives_variables.R . frm_fb_init_imputations.R . frm_fb_init_matrices_saved_parameters.R . frm_fb_initial_parameters.R . frm_fb_initial_parameters_se_sd_proposal.R . frm_fb_mh_refresh_imputed_values.R . frm_fb_mh_refresh_parameters.R . frm_fb_partable.R . frm_fb_refresh_parameters_step.R . frm_fb_sample_imputed_values.R . frm_fb_sample_imputed_values_eval_likelihood.R . frm_fb_sample_imputed_values_evaluate_mh_ratio.R . frm_fb_sample_imputed_values_proposal.R . frm_fb_sample_parameter_step.R . frm_fb_sample_parameters.R . frm_fb_sample_parameters_df_squeeze.R . frm_fb_sample_parameters_mh_acceptance_step.R . frm_fb_verbose_iterations.R . frm_fb_verbose_mh_refresh.R . frm_formula_character.R . frm_formula_extract_terms.R . frm_linreg_density.R . frm_linreg_sample_parameters.R . frm_logistic_density.R . frm_mdmb_regression_density.R . frm_mlreg_create_design_matrices.R . frm_mlreg_density.R . frm_mlreg_sample_parameters.R . frm_mlreg_wrapper_ml_mcmc.R . frm_modify_parameter_labels.R . frm_normalize_matrix_row.R . frm_normalize_posterior.R . frm_normalize_vector.R . frm_oprobit_density.R . frm_partable_thresholds.R . frm_prepare_data_em.R . frm_prepare_data_fb.R . frm_prepare_data_include_latent_data.R . frm_prepare_model_nodes_weights.R . frm_prepare_models.R . frm_prepare_models_descriptives.R . frm_prepare_models_design_matrices.R . frm_prepare_models_sigma_fixed.R . frm_proposal_refresh_helper.R . logLik_extract_ic.R . logLik_mdmb.R . logistic_regression.R . logthresh_2_thresh.R . mdmb_compute_df.R . mdmb_diff_quotient.R . mdmb_discretize.R . mdmb_dnorm.R . mdmb_exp_overflow.R . mdmb_extract_coef.R . mdmb_ginv.R . mdmb_lm_wfit.R . mdmb_oprobit_extend_thresh.R . mdmb_optim.R . mdmb_optim_control.R . mdmb_refresh_proposal_sd.R . mdmb_regression.R . mdmb_regression_R2.R . mdmb_regression_adjustment_differentiation_parameter.R . mdmb_regression_est_df_description.R . mdmb_regression_extract_parameters.R . mdmb_regression_ic.R . mdmb_regression_logistic_density.R . mdmb_regression_loglike_case.R . mdmb_regression_loglike_logpost.R . mdmb_regression_oprobit_density.R . mdmb_regression_optim_oprobit_fct.R . mdmb_regression_optim_oprobit_grad.R . mdmb_regression_optim_yjt_extract.R . mdmb_regression_optim_yjt_fct.R . mdmb_regression_optim_yjt_grad.R . mdmb_regression_predict.R . mdmb_regression_predict_yjt_bct.R . mdmb_regression_proc_control_optim_fct.R . mdmb_regression_summary.R . mdmb_regression_summary_table.R . mdmb_sample_missings.R . mdmb_sample_probabilities.R . mdmb_squeeze.R . mdmb_squeeze_double.R . mdmb_summary_print_computation_time.R . mdmb_summary_print_model_description.R . mdmb_vcov2se.R . mdmb_weighted_sd.R . mdmb_weighted_var.R . offset_values_extract.R . oprobit_regression.R . plot.frm_fb.R . predict.bct_regression.R . predict.logistic_regression.R . predict.oprobit_regression.R . predict.yjt_regression.R . rbct_scaled.R . remove_NA_data_frame.R . rt_scaled.R . ryjt_scaled.R . summary.bct_regression.R . summary.fit_bct_scaled.R . summary.fit_oprobit.R . summary.fit_t_scaled.R . summary.fit_yjt_scaled.R . summary.frm_em.R . summary.frm_fb.R . summary.logistic_regression.R . summary.oprobit_regression.R . summary.yjt_regression.R . vcov.mdmb.R . yj_adjust_lambda.R . yj_antitrafo.R . yj_trafo.R . yjt_regression.R . zzz.R .  Full mdmb package functions and examples
Downloads during the last 30 days
Get rewarded with contribution points by helping add
Reviews / comments / questions /suggestions ↴↴↴

Today's Hot Picks in Authors and Packages

WtTopsis  
Weighted Method for Multiple-Criteria Decision Making
Evaluation of alternatives based on multiple criteria using weighted technique for Order preference ...
Download / Learn more Package Citations See dependency  
convertid  
Convert Gene IDs Between Each Other and Fetch Annotations from Biomart
Gene Symbols or Ensembl Gene IDs are converted using the Bimap interface in 'AnnotationDbi' in conve ...
Download / Learn more Package Citations See dependency  
fastmit  
Fast Mutual Information Based Independence Test
A mutual information estimator based on k-nearest neighbor method proposed by A. Kraskov, et al. (20 ...
Download / Learn more Package Citations See dependency  
r2resize  
In-Text Resize for Images, Tables and Fancy Resize Containers in 'shiny', 'rmarkdown' and 'quarto' Documents
Automatic resizing toolbar for containers, images and tables. Various resizable or expandable contai ...
Download / Learn more Package Citations See dependency  
kesernetwork  
Visualization of the KESER Network
A shiny app to visualize the knowledge networks for the code concepts. Using co-occurrence matrices ...
Download / Learn more Package Citations See dependency  
cinaR  
A Computational Pipeline for Bulk 'ATAC-Seq' Profiles
Differential analyses and Enrichment pipeline for bulk 'ATAC-seq' data analyses. This package combi ...
Download / Learn more Package Citations See dependency  

23,580

R Packages

204,057

Dependencies

63,980

Author Associations

23,581

Publication Badges

© Copyright since 2022. All right reserved, rpkg.net.  Based in Cambridge, Massachusetts, USA