`subBoot`

now works with`glmerMod`

objects as well`reMargins`

a new function that allows the user to marginalize the prediction over breaks in the distribution of random effect distributions, see`?reMargins`

and the new`reMargins`

vignette (closes #73)

- Fixed an issue where known convergence errors were issuing warnings and causing the test suite to not work
- Fixed an issue where models with a random slope, no intercept, and no fixed term were unable to be predicted (#101)
- Fixed an issue with shinyMer not working with substantive fixed effects (#93)

- Parallel fitting of
`merModLists`

is now supported using the`future.apply`

package and the`future_lapply`

functions, optionally - Reduced package installation surface by eliminating unnecessary packages in the
`Suggests`

field

- Fixed a bug (#94) where
`predictInterval()`

would return a data.frame of the wrong dimensions when predicting a single row of observations for a`glm`

- Fixed a bug (#96) related to
`rstanarm`

dependencies in the package vignette - Switched from
`dontrun`

to`donttest`

for long-running examples (CRAN compliance) - Fixed and made more clear the generics applying to
`merModList`

objects (#92)

- Standard errors reported by
`merModList`

functions now apply the Rubin correction for multiple imputation

- Contribution by Alex Whitworth (@alexWhitworth) adding error checking to plotting functions
- The vignettes have been shortened and unit tests reorganized to facilitate Travis-CI builds and reduce CRAN build burden

- Added vignette on using multilevel models with multiply imputed data
- Added
`fixef`

and`ranef`

generics for`merModList`

objects - Added
`fastdisp`

generic for`merModList`

- Added
`summary`

generic for`merModList`

- Added
`print`

generic for`merModList`

- Documented all generics for
`merModList`

including examples and a new imputation vignette - Added
`modelInfo`

generic for`merMod`

objects that provides simple summary stats about a whole model

- Fix bug that returned NaN for
`std.error`

of a multiply imputed`merModList`

when calling`modelRandEffStats`

- Fixed bug in
`REimpact`

where some column names in`newdata`

would prevent the prediction intervals from being computed correctly. Users will now be warned. - Fixed bug in
`wiggle`

where documentation incorrectly stated the arguments to the function and the documentation did not describe function correctly

- Update the
`readme.rmd`

to package graphics with the R package, per CRAN

- Improve handling of formulas. If the original
`merMod`

has functions specified in the formula, the`draw`

and`wiggle`

functions will check for this and attempt to respect these variable transformations. Where this is not possible a warning will be issued. Most common transformations are respected as long as the the original variable is passed untransformed to the model. - Change the calculations of the residual variance. Previously residual variance was used to inflate both the variance around the fixed parameters and around the predicted values themselves. This was incorrect and resulted in overly conservative estimates. Now the residual variance is appropriately only used around the final predictions
- Rebuilt the readme.md to include new information about new features
- New option for
`predictInterval`

that allows the user to return the full interval, the fixed component, the random component, or the fixed and each random component separately for each observation - Fixed a bug with slope+intercept random terms that caused a miscalculation of the random component
- Add comparison to
`rstanarm`

to the Vignette - Make
`expectedRank`

output more`tidy`

like and allow function to calculate expected rank for all terms at once- Note, this breaks the API by changing the names of the columns in the output of this function

- Remove tests that test for timing to avoid issues with R-devel JIT compiler
- Remove
`plyr`

and replace with`dplyr`

- Fix issue #62
`varList`

will now throw an error if`==`

is used instead of`=`

- Fix issue #54
`predictInterval`

did not included random effects in calculations when`newdata`

had more than 1000 rows and/or user specified`parallel=TRUE`

. Note: fix was to disable the`.paropts`

option for`predictInterval`

… user can still specify for*temporary*backward compatibility but this should be either removed or fixed in the permanent solution. - Fix issue #53 about problems with
`predictInterval`

when only specific levels of a grouping factor are in`newdata`

with the colon specification of interactions - Fix issue #52 ICC wrong calculations … we just needed to square the standard deviations that we pulled

- Fix dependency on
`lme4`

to ensure compatibility with latest changes.

- 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

- Initial release

- 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