## Package News for 2016

### 2016-09-25: New Version Out (1.9-9)

After fixing some issues introduced by some non-backwards compatible changes in a package that metafor makes use of in a few places, I pushed out version 1.9-9 to CRAN (see here). So this is now the official (i.e., CRAN) release. This version includes many smaller tweaks and improvements, plus a few more noteworthy ones:

- Argument
`knha`

in`rma.uni()`

and argument`tdist`

in`rma.glmm()`

and`rma.mv()`

are now superseded by argument`test`

in all three functions. For backwards compatibility, the`knha`

and`tdist`

arguments still work, but are no longer documented. So, use`test="knha"`

or`test="t"`

instead. - One can now also obtain Cook's distances with
`cooks.distance()`

for`rma.mv`

objects. I will add the possibility to examine not only the influence of individual estimates but of multiple estimates later on (e.g., in the context of a multilevel meta-analysis, one may want to know what the influence is of all estimates within a group/cluster). Also, there are some other diagnostic measures that would be useful to add (especially`rstudent()`

). I hope to get around to this soon. - The
`permutest()`

function gains a`permci`

argument, which can be used to obtain permutation-based CIs of the model coefficients. Note that this is computationally very demanding and may take a long time to complete. - One can now obtain GOSH (i.e., graphical display of study heterogeneity) plots based on Olkin et al. (2012) with the
`gosh()`

function.

The full changelog can be found here.

The development version now carries version number 2.0-0, which will become the next official release once a sufficient number of updates have accumulated. Of course you can always just install the development version if you want to stay on top of those updates.

### 2016-09-20: Speeding Up Model Fitting

I've written up some notes on how to speed up model fitting when dealing with large datasets and/or models involving a large number of random effects. See here.

### 2016-08-01: Hunter and Schmidt Method

A question that comes up on a regular basis is how one can conduct meta-analyses using the 'Hunter and Schmidt method' using the metafor package. A discussion around this has been added to the tips and notes section. See here.

### 2016-07-07: I^2 for Multilevel and Multivariate Models

I've received several e-mails recently asking about generalizations of $I^2$ to multilevel and multivariate models. A discussion around this has been added to the tips and notes section. See here.

### 2016-05-22: Package Updates

I haven't made any entries here for a while, but development of the metafor package continues (time permitting) on the development version, which eventually will turn into release 1.9-9. Those who would like to play around with the development version already can just install it directly from GitHub with `remotes::install_github("wviechtb/metafor")`

(need to install remotes first of course). You can also track changes and follow the development by going to the GitHub repository for the package.

Besides a lot of smaller tweaks and improvements, some of the more interesting changes are the addition of GOSH plots (you can see an example already here), `cooks.distance()`

for `rma.mv`

objects (useful for examining the data for influential cases), and the ability to get permutation-based CIs with `permutest()`

(which is computationally rather demanding).

I am also slowly increasing the code coverage of the automated package tests. At the moment, coverage is just a wee bit shy of 80% (see here for detail).