I have recently discovered `memisc`

, an extremely useful **R **package by Martin Elff (see his `memisc`

page here). The package contains any number of useful functions, and is particularly good at helping one manage and recode survey data. However, by far my favorite thing about the package is the `mtable()`

function. `mtable()`

makes it easy to compare the results from different models from within **R** and, along with `toLatex()`

, makes it easy create \(\text{\LaTeX{}}\) tables. Unfortunately, the functions that parse `lme4`

model objects is out-dated. The code below updates them for the current release version of `lme4`

. A couple things to note, however: first, these functions do not work with model objects created by `lme4a`

, which are significantly different than those produced in `lme4`

; and second, the `getSummary.mer()`

function currently only reports the results from two-level models, though extending it shouldn’t be too difficult.

- Script: mtable-lme4

Great blog – very helpful! I hadn’t seen the memisc package before.

On this topic – since you’ve IV’s at one of your categories, I thought I’d ask: do you know if there’s a way to get tsls (using the sem package) estimates from R to work with the memisc package?

Hello John, sorry for the delay in responding.

I actually haven’t tried to get memisc and sem to play together. I don’t do much with sem, so never thought to spend the time. It shouldn’t be too hard to implement basic support, though.

Hi

First of all, thank you for the script. I do have a quick question about your calculation of the p-values. I was trying to debug why I was getting strange output tables on my results and was wondering if I am making a mistake.

As you calculate it, the normal does not take the absolute value of the t-value , and therefore gives you strange results when the initial model produces negative t-values.

In particular I mean this part:

p <- (1 – pnorm(smry@coefs[, 3])) * 2

Am I missing something?

Thank you,

Christoph

Ah nevermind. I just saw that you updated the code in the full package.

Thank you again, this function saved A LOT of time for me.

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