Time for the seventh iteration!

To remind for those who are new to the idea:

  • CVJC is a meeting on chat where we discuss some paper and its theoretical/practical surroundings.
  • It usually takes place on Friday about 18:00UTC.
  • The paper must be OpenAccess or a (p)reprint suggested previously on a meta thread like this one and selected in voting.
  • We will try to invite the author(s).

So, please suggest papers (each in one answer), and vote for your favourites!

EDIT: I see there are new suggestions coming, so maybe it is time to call the whole thing rebooted and set a new deadline to 23:59UTC 11.11.2012. For a fair voting, chl's suggestion gets -5 vote normalisation.

EDIT: Paper selected; as usual I'll try to invite the authors and then schedule the meeting.

EDIT: The 7th CVJC featuring Handling Missing Data by Maximum Likelihood by Paul D. Allison will take place on Friday 12.14.2012 at 16:00 UTC. You can register here.

Can we make the next paper chosen language agnostic. I can follow the code and function calls, but it's not as pleasant. – Cam.Davidson.Pilon Dec 14 '12 at 0:20
I registered, but how can I see the discussion ? – Joe King Dec 14 '12 at 16:50

3 Answers 3

up vote 7 down vote accepted

I would like to propose the following article:

Paper 312-2012 
Handling Missing Data by Maximum Likelihood  
Paul D. Allison, Statistical Horizons, Haverford, PA, USA


Missing data seems to be an area in which all applied statisticians are, or should be, interested (I hope this is not a controversial statement!), and perhaps some theoreticians are interested also :-)


I would like to propose the following article:

Sheehan NA, Didelez V, Burton PR, Tobin MD (2008) Mendelian Randomisation and Causal Inference in Observational Epidemiology. PLoS Med 5(8): e177. doi:10.1371/journal.pmed.0050177

This paper is of some interest in relation to some threads on this site, in particular those related to inferring causality from observational studies.


I would like to suggest: A Better Lemon Squeezer: Maximum Likelihood Regression with Beta-Distributed Dependent Variables

This will be especially useful for DVs that have ceiling or floor effects or that are bounded, it is also useful when the variance may differ as a result of the IVs. But the paper gets kind of technical.

I've seen this paper come up a few times, not just in Peter Flom's answers, and wanted to second this suggestion for the next journal club. In that vein, is one on the horizon? – Matt Krause Feb 13 '13 at 17:34

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