Changes in version 0.6.1 (2026-03-17) o 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 o 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 o Added full_detrend argument to mlVAR() for removing systematic occasion effects (e.g., time-of-day trends) before estimation Changes in version 0.6 o 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 o 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. o Added resimulate() S3 method for mlVAR objects: generates simulated data from a fitted model using person-specific parameters for posterior predictive checks o Rewrote residuals() S3 method for mlVAR objects as a wrapper around predict(), now supporting scale_back and include_ids arguments o Added .groups = "drop" to all grouped summarise/summarize calls to suppress dplyr 1.0.0+ lifecycle warnings o Fixed bug in Stepwise(): selected wrong model at each iteration step o Fixed bug in importMplus: temporal fixed effects were only extracted for the first outcome variable o Fixed bug in Mplus correlation samples: all samples were computed from the 3rd sample instead of each respective sample o Fixed bug in mlVARsample: subjects with improper or non-stationary models were not correctly excluded from simulation o Added iteration cap (1000) to mlVARsim repeat loop to prevent infinite loops when stable parameters cannot be generated o Minor: avoided redundant eigendecomposition in forcePositive() Changes in version 0.5.5 (2026-02-06) o Fixed R CMD check NOTE: no visible binding for global variable 'id' in movingWindow o Replaced deprecated dplyr functions: summarize_each/funs() with across(), summarise_each_() with across(), filter_() with filter() o Removed library() calls from parSim.R o Removed stringsAsFactors argument from cbind() calls in NodeWise.R (had no effect) o Replaced plyr::ddply and plyr::join with dplyr equivalents; removed plyr dependency o Fixed unreachable code after stop() in mlVAR (changed to warning) o Fixed duplicate return statement in randomEffects o Cleaned up NAMESPACE: removed duplicate export and unused plyr imports o Minimum dplyr version bumped to >= 1.0.0 Changes in version 0.5.4 o mlVAR with lmer estimation now returns 'step1_residuals' in the output Changes in version 0.5.3 o Random effect SDs of Gamma_theta stored in $results$Gamma_Theta$SD are now based on analytric standard deviations Changes in version 0.5.2 (2024-02-01) o Removed deprecated function mlVARsim0 Changes in version 0.5.1 (2023-05-16) o Fixed remaining deprecated dplyr functions Changes in version 0.5 (2021-10-25) o The 'mlVARsample' function has been added to mlVAR o Added Myrthe Veenman to contributor list o Fixed a bug where contemporaneous standard deviations were reported as variances instead of standard deviations o Fixed a bug with the beepvar argument o Replaced deprecated dplyr functions o Added a warning for when a beep is used multiple times o The 'nonsig' argument in the plot method now defaults to 'show' when SD=TRUE o Fixed a bug in the summary method when fixed effects estimation was used Changes in version 0.4.3 (2019-06-20) 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 (2019-01-24) o Contemporaneous multi-level models are now returned in the output Changes in version 0.4.1 (2018-08-26) 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 (2017-09-02) 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 (2017-03-28) 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 (2016-07-04) 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