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.

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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

http://www.statisticalhorizons.com/wp-content/uploads/MissingDataByML.pdf

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 :-)

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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.

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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.

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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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