NEWS
mlVAR 0.6.1 (2026-03-17)
- Fixed resimulate(): person-specific means are now computed as stationary means (I - B_between)^{-1} * alpha_i rather than using the raw lmer intercept, which was incorrect when between-person predictors are uncentered
- Added resimulate() arguments: nTime for simulating custom-length time series per person, keep_missing to toggle whether the original variable-level missingness pattern is applied, and variance ("model" or "empirical") to choose between model-implied or person-specific empirical innovation covariance
- Added full_detrend argument to mlVAR() for removing systematic occasion effects (e.g., time-of-day trends) before estimation
mlVAR 0.6
- Added mlGGM() function for multi-level Gaussian Graphical Model estimation using single-step nodewise regression, simultaneously estimating within-cluster and between-cluster partial correlation networks from cross-sectional multilevel data
- Added predict() S3 method for mlVAR objects: returns fitted values, residuals, and observed data aligned to original input data (with NAs for unpredictable rows). Supports scale_back argument to return values on original data scale, include_ids to include id/day/beep columns, and newdata for out-of-sample predictions. Works with both lmer and lm estimators.
- Added resimulate() S3 method for mlVAR objects: generates simulated data from a fitted model using person-specific parameters for posterior predictive checks
- Rewrote residuals() S3 method for mlVAR objects as a wrapper around predict(), now supporting scale_back and include_ids arguments
- Added .groups = "drop" to all grouped summarise/summarize calls to suppress dplyr 1.0.0+ lifecycle warnings
- Fixed bug in Stepwise(): selected wrong model at each iteration step
- Fixed bug in importMplus: temporal fixed effects were only extracted for the first outcome variable
- Fixed bug in Mplus correlation samples: all samples were computed from the 3rd sample instead of each respective sample
- Fixed bug in mlVARsample: subjects with improper or non-stationary models were not correctly excluded from simulation
- Added iteration cap (1000) to mlVARsim repeat loop to prevent infinite loops when stable parameters cannot be generated
- Minor: avoided redundant eigendecomposition in forcePositive()
mlVAR 0.5.5 (2026-02-06)
- Fixed R CMD check NOTE: no visible binding for global variable 'id' in movingWindow
- Replaced deprecated dplyr functions: summarize_each/funs() with across(), summarise_each_() with across(), filter_() with filter()
- Removed library() calls from parSim.R
- Removed stringsAsFactors argument from cbind() calls in NodeWise.R (had no effect)
- Replaced plyr::ddply and plyr::join with dplyr equivalents; removed plyr dependency
- Fixed unreachable code after stop() in mlVAR (changed to warning)
- Fixed duplicate return statement in randomEffects
- Cleaned up NAMESPACE: removed duplicate export and unused plyr imports
- Minimum dplyr version bumped to >= 1.0.0
mlVAR 0.5.4
- mlVAR with lmer estimation now returns 'step1_residuals' in the output
mlVAR 0.5.3
- Random effect SDs of Gamma_theta stored in $results$Gamma_Theta$SD are now based on analytric standard deviations
mlVAR 0.5.2 (2024-02-01)
- Removed deprecated function mlVARsim0
mlVAR 0.5.1 (2023-05-16)
- Fixed remaining deprecated dplyr functions
mlVAR 0.5 (2021-10-25)
- 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
mlVAR 0.4.3 (2019-06-20)
- mlVAR now issues a warning when < 20 observations per subject are used
- Fixed a bug with 'lmerResults2'
- Now suppressing warnings and messages from lmer
- Added a progress bar for computing random effects
mlVAR 0.4.2 (2019-01-24)
- Contemporaneous multi-level models are now returned in the output
mlVAR 0.4.1 (2018-08-26)
- mlVAR now uses correlations of residuals as estimate for the contemporaneous correlation matrix (not partial) if estimated inverse covariance matrix is not properly invetable
- Added mlVARsample function to run a simulation study
given a mlVAR object.
- Fixed a bug with estimator = "mPlus"
- mlVAR now gives a warning when between-subject networks could not be computed, rather than breaking with an uninformative error.
mlVAR 0.4 (2017-09-02)
- Added AR argument to mlVAR to fit AR models only
- estimator = "Mplus" is now supported! Requires Mplus 8 to be installed.
- Several arguments have been added to mlVAR to handle Mplus estimation
mlVAR 0.3.3 (2017-03-28)
- The plot method for mlVAR sim objects now uses nonsig = "show"
- plot method now uses nonsig = "show" by default!
- Summary method now shows p-values for contemporaneous effects
- Several small bugfixes
mlVAR 0.3.1 (2016-07-04)
- The 'partial' argument in 'plot.mlVAR' now defaults to TRUE
- Added 'contemporaneous' argument to mlVAR
- Added 'lm' estimator for fitting unique VAR models per subject
- Added 'rule' argument to plot.mlVAR to set the rule of choosing significance in nodewise GGM estimation
mlVAR 0.3
- Complete rework of package!
- mlVAR, mlVARsim, and relevant methods have been completely rewritten
- Now support contemporaneous effects and between-subjects effects
- Old functions are now labeled mlVAR0, mlVARsim0, etcetera