+++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ ------------------------- mdmb NEWS --------------------------- +++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ |\ /||~~\ |\ /||~~\ | \/ || || \/ ||--< | ||__/ | ||__/ mdmb: Model Based Treatment of Missing Data Alexander Robitzsch & Oliver Luedtke Questions or suggestions about mdmb should be sent to robitzsch@leibniz-ipn.de In case of reporting a bug, please always provide a reproducible script. +++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ CHANGELOG mdmb ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ --------------------------------------------------------------------- VERSIONS mdmb 1.8 | 2023-02-28 | Last: mdmb 1.8-7 --------------------------------------------------------------------- FIXED * now ouput observed log-likelihood value and not expected log-likelihood (thanks to Paul Allison) DATA * included/modified datasets: --- EXAMP * included/modified examples: --- --------------------------------------------------------------------- VERSIONS mdmb 1.7 | 2023-02-17 | Last: mdmb 1.7-22 --------------------------------------------------------------------- FIXED * fixed a bug in standard error computation in frm_em() if the logistic model was involved (thanks to Craig Enders and Paul Allison) ADDED * included argument 'update_model' in frm_em() DATA * included/modified datasets: --- EXAMP * included/modified examples: --- --------------------------------------------------------------------- VERSIONS mdmb 1.6 | 2022-05-17 | Last: mdmb 1.6-5 --------------------------------------------------------------------- FIXED * fixed a bug in frm_fb() for sampling of variables at higher levels with probit model (thanks to Simon Grund) DATA * included/modified datasets: --- EXAMP * included/modified examples: --- --------------------------------------------------------------------- VERSIONS mdmb 1.5 | 2021-01-21 | Last: mdmb 1.5-8 --------------------------------------------------------------------- FIXED * fixed a bug in sampling imputed values in frm_fb() for model 'yjtreg' with argument 'probit=TRUE' (thanks to Simon Grund) FIXED * fixed a bug in frm_fb() function when using multilevel models and the argument 'inits_lme4=FALSE' (thanks to Rushani Wijesuriya) DATA * included/modified datasets: --- EXAMP * included/modified examples: --- --------------------------------------------------------------------- VERSIONS mdmb 1.4 | 2020-05-11 | Last: mdmb 1.4-12 --------------------------------------------------------------------- NOTE * included data checks about variable ordering and sampling level in frm_fb() and frm_em() (thanks to a discussion with Sebastian Roehl) DATA * included/modified datasets: --- EXAMP * included/modified examples: --- --------------------------------------------------------------------- VERSIONS mdmb 1.3 | 2019-04-16 | Last: mdmb 1.3-18 --------------------------------------------------------------------- NOTE * included option for changing prior distributions in frm_fb() for multilevel models (requested by Simon Grund) NOTE * removed dependency from lme4::lmer() function for generating initial values for multilevel models in frm_fb() (due to a discussion with Simon Grund) NOTE * updated 'mlreg' function in frm_fb() for argument 'ridge' which was introduced in miceadds::ml_mcmc(). This option needs miceadds >= 3.2-10. NOTE * fixed an issue in initial value computation in frm_fb() for models with dependent variables at higher levels (thanks to Simon Grund) DATA * included/modified datasets: --- EXAMP * included/modified examples: frm (10.3) --------------------------------------------------------------------- VERSIONS mdmb 1.2 | 2019-01-11 | Last: mdmb 1.2-4 --------------------------------------------------------------------- FIXED * fixed a bug in frm_fb() which caused crash of algorithm (thanks to Simon Grund) DATA * included/modified datasets: --- EXAMP * included/modified examples: --- --------------------------------------------------------------------- VERSIONS mdmb 1.1 | 2019-01-07 | Last: mdmb 1.1-51 --------------------------------------------------------------------- NOTE * efficiency improvements in internal function fit_mdmb_distribution() ADDED * added argument 'est_df' in yjt_regression() and bct_regression() for estimation of degrees of freedom in t distribution. These models can also be used in the sequential modeling frm_fb() and frm_em() (see ?frm_fb; Example 12) NOTE * corrected labeling of variables in coda summary output of frm_fb() function ADDED * allowed now optimizers stats::optim() and stats::nlminb() in mdmb_regression() and frm_em(). The optimizer can be chosen by the argument 'optimizer'. DATA * included/modified datasets: --- EXAMP * included/modified examples: mdmb_regression (2), frm_fb (12) --------------------------------------------------------------------- VERSIONS mdmb 1.0 | 2018-11-06 | Last: mdmb 1.0-18 --------------------------------------------------------------------- FIXED * fixed a bug in frm_em() and frm_fb() when logistic regression is applied (occured in Example 8; thanks to Man Yiu Tim Tsang) FIXED * fixed bug in frm_em() and frm_fb() for ordinal probit regression and other models (Example 10; thanks to Man Yiu Tim Tsang). The bug was introduced by allowing probit transformation in Yeo-Johnson regression function yjtreg(). FIXED * fixed bug in sampling of linear regression with no estimated mean structure (Example 9) DATA * included/modified datasets: --- EXAMP * included/modified examples: --- --------------------------------------------------------------------- VERSIONS mdmb 0.11 | 2018-10-16 | Last: mdmb 0.11-7 --------------------------------------------------------------------- NOTE * included consistency checks of model names for covariate models in frm_em() and frm_fb() NOTE * fixed an error in mdmb_regression() for Yeo-Johnson transformed variables (incompatible dimensions) DATA * included/modified datasets: --- EXAMP * included/modified examples: --- --------------------------------------------------------------------- VERSIONS mdmb 0.10 | 2018-09-12 | Last: mdmb 0.10-13 --------------------------------------------------------------------- NOTE * included argument 'control_optim_fct' in oprobit_regression(). Slight speed improvements in case of many ordered categories. FIXED * fixed a recently introduced bug for linear regression models in frm_fb() DATA * included/modified datasets: --- EXAMP * included/modified examples: --- --------------------------------------------------------------------- VERSIONS mdmb 0.9 | 2018-08-08 | Last: mdmb 0.9-43 --------------------------------------------------------------------- ADDED * extended Yeo-Johnson transformation to include bounded variables on [0,1] by employing a probit transformation. The extension is implemented in fit_yjt_scaled(), yjt_regression(), frm_em() and frm_fb(). DATA * included/modified datasets: data.mb05 EXAMP * included/modified examples: yjt_dist (6), frm_em (11) --------------------------------------------------------------------- VERSIONS mdmb 0.8 | 2018-07-09 | Last: mdmb 0.8-47 --------------------------------------------------------------------- ADDED * included option for Gibbs sampling in frm_fb() which can be enabled by the argument 'use_gibbs' ADDED * included multilevel regression for normally distributed and ordinal data in frm_fb() (model 'mlreg') DATA * included/modified datasets: data.mb04 EXAMP * included/modified examples: frm (10) --------------------------------------------------------------------- VERSIONS mdmb 0.7 | 2018-04-24 | Last: mdmb 0.7-19 --------------------------------------------------------------------- NOTE * included argument 'as_mids' for conversion into mids objects in frm2datlist() NOTE * translated some parts of calculations in frm_em() into Rcpp DATA * included/modified datasets: --- EXAMP * included/modified examples: --- --------------------------------------------------------------------- VERSIONS mdmb 0.6 | 2018-02-16 | Last: mdmb 0.6-17 --------------------------------------------------------------------- FIXED * fixed bug in oprobit_regression() when no regression coefficients were estimated in the model FIXED * fixed incorrect matching of MCMC diagnostics informations in summary output FIXED * included correct labelling in frm_em() and frm_fb() if classes 'yjtreg' and 'bctreg' are used NOTE * included dataset data.mb03 from Enders et al. (2014, PsychMeth) FIXED * fixed problems in numerical overflow when calculating Metropolis-Hasting ratios in frm_fb() DATA * included/modified datasets: data.mb03 EXAMP * included/modified examples: data.mb (1) --------------------------------------------------------------------- VERSIONS mdmb 0.5 | 2018-01-22 | Last: mdmb 0.5-27 --------------------------------------------------------------------- ADDED * added example for modelling nonignorable data with frm_em() (see Example 8 in 'frm.Rd') ADDED * added ordinal probit distribution fit_oprobit() and ordinal probit regression oprobit_regression(). ADDED * extended frm_em() and frm_fb() functions to ordinal data NOTE * fixed incorrect variable names in parts of the MCMC summary output in frm_fb() DATA * included/modified datasets: --- EXAMP * included/modified examples: frm (8), oprobit_dist (1), mdmb_regression (4), frm (9) --------------------------------------------------------------------- VERSIONS mdmb 0.4 | 2017-08-20 | Last: mdmb 0.4-15 --------------------------------------------------------------------- NOTE * speeded data processing in frm_em() NOTE * included Example 1.3 in frm() using the jomo package for imputation under a substantive model containing interaction effects NOTE * included example for estimation of model including latent interaction effects with frm_em() function NOTE * included argument 'log' in dt_scaled(), dbct_scaled() and dyt_scaled() NOTE * included more efficient computation of gradient in logistic_regression(), bct_regression() and yjt_regression(). Different computation methods can be chosen by the argument 'use_grad'. These gradients are now also used in frm_em() which results in some speed improvement. NOTE * changed initial values in logistic_regression(), bct_regression() and yjt_regression() to least-squares solutions DATA * included/modified datasets: --- EXAMP * included/modified examples: frm (1.3, 7) --------------------------------------------------------------------- VERSIONS mdmb 0.3 | 2017-07-12 | Last: mdmb 0.3-11 --------------------------------------------------------------------- NOTE * changed default in 'nodes_control' in 'frm_em' to use a wider integration grid for missing values NOTE * added information about standard error calculation in 'frm_em'; reference Jamshidian and Jennrich (2000, JRSSB) FIXED * fixed an error in the 'frm_em' function which was not yet applicable for 'yjtreg' regression models DATA * included/modified datasets: --- EXAMP * included/modified examples: --- --------------------------------------------------------------------- Versions 0.2 -- 2017-02-07 -- CRAN mdmb 0.2-0 --------------------------------------------------------------------- FIXED * fixed an error in initialization of sigma parameter in mdmb::frm_fb function with 'linreg' imputation DATA * included/modified datasets: --- EXAMP * included/modified examples: --- --------------------------------------------------------------------- Versions 0.1 -- 2017-01-25 -- CRAN mdmb 0.1-0 --------------------------------------------------------------------- INIT * initial version of the package ADDED * added functions for scaled t distribution with Yeo-Johnson transformation ('d_yjt_scaled', 'fit_yjt_scaled') and Box-Cox transformation ('d_bct_scaled', 'fit_bct_scaled') ADDED * added additional regression functions 'logistic_regression', 'yjt_regression' and 'bct_regression' ADDED * added function 'frm_em' for maximum likelihood estimation of regression models with missing covariates ADDED * added function 'frm_fb' for fully Bayesian estimation of regression models with missing covariates. Imputations of missing values are provided. NOTE * included utility functions 'eval_prior_list', 'eval_prior_list_sumlog', 'offset_values_extract' and 'remove_NA_data_frame' DATA * included/modified datasets: data.mb01, data.mb02 EXAMP * included/modified examples: mbmb_regression (1,2,3,4,5), frm (1,2,3,4,5), yjt_dist (1,2,3,4,5)