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