NEWS

merTools 0.2.1

Coerce dplyr tbl and tbl_df objects to data.frames when they are passed to predictInterval and issue a warning
Try to coerce other data types passed to newdata in predictInterval before failing if coercion is unsuccessful
Numeric stabilization of unit tests by including seed values for random tests
Fix handling of models with nested random effect terms (GitHub #47)
Fix vignette images

Substantial performance enhancement for predictInterval which includes better handling of large numbers of parameters and simulations, performance tweaks for added speed (~10x), and parallel backend support (currently not optimized)
Add support for probit models and limited support for other glmm link functions, with warning (still do not know how to handle sigma parameter for these)
Add ability for user-specified seed for reproducibility
Add support for blmer objects from the blme package
Add a merModList object for lists of merMod objects fitted to subsets of a dataset, useful for imputation or for working with extremely large datasets
Add a print method for merModList to mimic output of summary.merMod
Add a VarCorr method for merModList
Add new package data to demonstrate replication from selected published texts on multilevel modeling using different software (1982 High School and Beyond Survey data)

Changed the default n.sims for the predictInterval function from 100 to 1,000 to give better coverage and reflect performance increase
Changed the default for level in predictInterval to be 0.8 instead of 0.95 to reflect that 0.95 prediction intervals are more conservative than most users need

For the next release (1.0) we are considering a permanent switch to C++ RMVN sampler courtesy of Giri Gopalan 's excellent FastGP package

Provides predictInterval to allow prediction intervals from glmer and lmer objects
Provides FEsim and REsim to extract distributions of model parameters
Provides shinyMer an interactive shiny application for exploring lmer and glmer models
Provides expectedRank function to interpret the ordering of effects
Provides REimpact to simulate the impact of grouping factors on the outcome
Provides draw function to allow user to explore a specific observation
Provides wiggle function for user to build a simulated set of counterfactual cases to explore