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------------------------- mdmb NEWS ---------------------------

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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.

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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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)
