Social Science Statistics Blog

8 May 2008

Some Random Notes about the International Network Meeting

Last week we had an International Meeting on Methodology for Empirical Research on Social Interactions, Social Networks, and Health here at the IQ., thanks to the organization by Professor Charles Manski and Professor Nicholas Christakis. Some people told me that the second day of the meeting was much more “violent” than the first day and based on what I have seen, I believe it was true. I saw at least three cliques of speakers were automatically formed on site along the disciplinary lines: statisticians, economists, and sociologists and political scientists. There were even sub-cliques and backfires! Fortunately, nobody was severely wounded. But anyway, it was a great intellectual exchange between disciplines. Below are some brief notes I took at the second day of the meeting, particularly at the last 20 minutes of the meeting when speakers talked about the future directions of network analysis in social sciences. Sorry for that I forgot to jot down exactly who said what, and that I also squeezed into the notes some of my personal thoughts. I took full responsibility for all errors in the notes.

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Posted by Weihua An at 10:46 AM | Comments (0) | TrackBack (0)

7 May 2008

What's New in Econometrics

Here's a link to a free, 18-hour mini-course on recent advances in econometrics and statistics from the National Bureau of Economic Research. It's co-taught by Guido Imbens and Jeffrey Wooldridge. The intended audience is obviously economists, but there are several topics (Bayesian inference, missing data, etc.) that are likely of interest to a wide range of social scientists. The course includes lecture videos, slides, as well as detailed notes on each topic.

Posted by John Graves at 1:53 PM | Comments (0)

Plotting Survival Curves with Uncertainty Estimates

One of the pesky things I've found in my (limited) experience with survival analysis is that it's almost impossible to plot several survival curves in the same space and include measures of uncertainty without the entire plot becoming incomprehensible. So, to build on the great R discussions Ellie and Andy have provided in recent blog posts, I'd like to offer an extension of my own. I've created a fairly flexible function that allows one to plot several survival curves along with estimation uncertainty from Zelig's Cox proportional hazards output (which was developed by Patrick Lam). Here are two examples of what my surv.plot() function can provide:

Hopefully this will be of some interest to a few readers. More details and example code below.

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Posted by John Graves at 11:48 AM | Comments (0)

6 May 2008

Tuesday: Tips & Tricks

I've been programming in R for four years now, and it seems that no how much I learn there are a million tiny ways that I could do it better. We all have our own programming styles and frequently used functions that may prove useful to others. I often find that a casual conversation with an office mate yields new approaches to a programming quandary. I'm speaking not of statistical insights, though those are important too, but rather the "simple" art of data manipulation and programming implementation--those essential tricks that help to improve coding efficiency. So, to that end I'm announcing the beginning of a bi-weekly "Tuesday Tips & Tricks" posting. These tips may include the description of a useful and perhaps obscure function, or the solutions to common coding problems. I'm selfishly hoping that if readers of this blog know of better or alternate approaches, they'll respond in the comment section. So I'm looking forward to reading your responses.

This week's tip: How to quickly summarize contents of an object.

Answer: summary(), str(), dput()

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Posted by Eleanor Neff Powell at 4:41 PM | Comments (3)

4 May 2008

IN, NC Predictions

Since I have qualifying exams tomorrow, I'll keep this entry unimaginative. I've re-run my predictions for the Indiana and North Carolina primaries on Tuesday, adding a few new bells and whistles:

• A turnout model
• More covariates in the voting share model

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Posted by Kevin Bartz at 6:38 PM | Comments (4)

1 May 2008

New NBER working paper by James Heckman ``Econometric Causality''

James Heckman has a new NBER working paper ``Econmetric Causality’’ which some of you might interesting. To give you a flavor, Heckman writes

``Unlike the Neyman–Rubin model, these [selection] models do not start with the experiment as an ideal but they start with well-posed, clearly articulated models for outcomes and treatment choice where the unobservables that underlie the selection and evaluation problem are made explicit. The hypothetical manipulations define the causal parameters of the model. Randomization is a metaphor and not an ideal or “gold standard".’’ (page 37)

Heckman, J (2008) ``Econometric Causality’’ NBER working paper #13934. http://papers.nber.org/papers/W13934

Abstract: This paper presents the econometric approach to causal modeling. It is motivated by policy problems. New causal parameters are defined and identified to address specific policy problems. Economists embrace a scientific approach to causality and model the preferences and choices of agents to infer subjective (agent) evaluations as well as objective outcomes. Anticipated and realized subjective and objective outcomes are distinguished. Models for simultaneous causality are developed. The paper contrasts the Neyman-Rubin model of causality with the econometric approach.

Posted by Sebastian Bauhoff at 10:00 AM | Comments (0)

29 April 2008

Common sense and research design

Last week on the New York Times' "Well" blog, Tara Parker-Pope blogged about a study that appeared to show that a mother's diet can affect the sex of her child. Yes, the father's sperm determines the gender of a particular embryo, but the story is that the mother's nutritional intake can affect how likely a given embryo is to go to term. At any rate the study is based on survey data in which mothers of boys report eating more around the time of conception than mothers of girls.

I can't really pass judgment on the study itself -- I haven't had time to read the thing -- but as someone who is pretty obsessed with (and professionally involved in) criticizing causal inferences drawn from observational studies, I found it pretty entertaining to read the comments. I admit I did not read all 409 of them. But on the whole they fell into five categories:

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Posted by Andy Eggers at 4:36 PM | Comments (1)

28 April 2008

Jamie Robins on "Estimation of Direct Effects in Different Contexts"

Please join us for the final applied statistics workshop when Jamie Robins , Department of Epidemiology and Biostatistics, Harvard School of Public Health, will Present "Estimation of Direct Effects in different contexts: Pure and natural direct effects, Pathway-specific estimation, principal stratification, mendelian randomization, testing the exclusion restriction , and surrogate markers". Jamie will be sampling from the following papers during his talk:

paper 1
paper 2
paper 3
paper 4

The Applied Statistics workshop meets in room N-354, CGIS-Knafel 1737 Cambridge. The workshop begins at 12noon with a light lunch, with our presentations beginning at 1215 and usually ending around 130 pm.

Posted by Justin Grimmer at 10:48 PM | Comments (0)

24 April 2008

FAQs about Statistical Interactions

I am writing a short essay about the connection and distinction between indirect effect and interaction effect for a methodological class and find the following website very helpful to clarify some of the FAQs on that subject. The website is maintained by Professor Regina Branton at the Department of Political Science of Rice University.

http://www.ruf.rice.edu/~branton/interaction/faqshome.htm

Also check out the mediation item at Wikipedia and its great references.

http://en.wikipedia.org/wiki/Mediation_(statistics)

Posted by Weihua An at 11:35 AM | Comments (5)

22 April 2008

Predicting Pennsylvania, Updated

Update: Check out how my predictions fared! Two comparisons are given, one showing both maps in the same image and one as an animated GIF (kudos to the animation package in R).

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Posted by Kevin Bartz at 11:16 AM | Comments (5)