Changes in Version 0.5.2 - Removed deprecated function mlVARsim0 Changes in Version 0.5.1 - Fixed remaining deprecated dplyr functions Changes in Version 0.5 - The 'mlVARsample' function has been added to mlVAR - Added Myrthe Veenman to contributor list - Fixed a bug where contemporaneous standard deviations were reported as variances instead of standard deviations - Fixed a bug with the beepvar argument - Replaced deprecated dplyr functions - Added a warning for when a beep is used multiple times - The 'nonsig' argument in the plot method now defaults to 'show' when SD=TRUE - Fixed a bug in the summary method when fixed effects estimation was used Changes in version 0.4.3 o mlVAR now issues a warning when < 20 observations per subject are used o Fixed a bug with 'lmerResults2' o Now suppressing warnings and messages from lmer o Added a progress bar for computing random effects Changes in version 0.4.2 o Contemporaneous multi-level models are now returned in the output Changes in version 0.4.1 o mlVAR now uses correlations of residuals as estimate for the contemporaneous correlation matrix (not partial) if estimated inverse covariance matrix is not properly invetable o Added mlVARsample function to run a simulation study given a mlVAR object. o Fixed a bug with estimator = "mPlus" o mlVAR now gives a warning when between-subject networks could not be computed, rather than breaking with an uninformative error. Changes in version 0.4 o Added AR argument to mlVAR to fit AR models only o estimator = "Mplus" is now supported! Requires Mplus 8 to be installed. o Several arguments have been added to mlVAR to handle Mplus estimation Changes in version 0.3.3 o The plot method for mlVAR sim objects now uses nonsig = "show" o plot method now uses nonsig = "show" by default! o Summary method now shows p-values for contemporaneous effects o Several small bugfixes Changes in version 0.3.1 o The 'partial' argument in 'plot.mlVAR' now defaults to TRUE o Added 'contemporaneous' argument to mlVAR o Added 'lm' estimator for fitting unique VAR models per subject o Added 'rule' argument to plot.mlVAR to set the rule of choosing significance in nodewise GGM estimation Changes in version 0.3 o Complete rework of package! o mlVAR, mlVARsim, and relevant methods have been completely rewritten o Now support contemporaneous effects and between-subjects effects o Old functions are now labeled mlVAR0, mlVARsim0, etcetera