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    Voter Outrage over Health Care

    Political scientists David Brady and Doug Rivers, along with business and law professor Daniel Kessler wrote an op-ed for the WSJ arguing that the health care bill is hurting the Democrats. Their evidence is that states with lower support for the bill also have lower support for incumbent Democratic senatorial candidates:

    Health reform is more popular in some of these states than in others. Where it's popular, Democratic candidates don't have too much of a problem, but where it's...
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    Was there Really a Hawthorne Effect at the Hawthorne Plant?

    The idea of the Hawthorne effect is that individuals may change their behavior because they are being studied, in addition to any real effects of the intervention. Steven Levitt and John List have revisited the illumination experiments at the Hawthorne plant that gave name to the effect, and argue that many of the original conclusions do not hold up to scrutiny. There's an Economist article on the paper here but its subtitle...

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    Welcome

    Welcome to the Social Science Statistics Blog, hosted by the Institute for Quantitative Social Science at Harvard University. We are starting this blog today in order to make public some of the hallway conversations about social science statistical methods and analysis that are regular features at the Institute and related research groups. Perhaps you may have also found that while formally published research is emphasizing one topic or approach, conversations with scholars at conferences reveal a strong...

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    Western on "Analyzing Inequality with Variance Function Regressions"

    Please join us this Wednesday, February 11th when Bruce Western, Professor of Sociology, will present "Analyzing Inequality with Variance Function Regressions". Bruce provided the following abstract:

    Regression-based studies of inequality model only between-group differences, yet often these differences are far exceeded by residual inequality. Residual inequality is usually attributed to measurement error or the influence of unobserved characteristics. We present a regression that includes covariates for both the mean and variance of a dependent variable. In this model, the...

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    What's an Effect

    Felix Elwert

    Though it hardly comports with my own views, there are plenty of people in the social sciences and economics that are troubled by the potential outcomes framework of causality. What intrigues me about this opposition is that most of those who object to the notion of causality appear comfortable with talk about regression “effects.��?

    If you object to talk about causality, what do you mean by “effect��??

    By way of preemptive self-defense, this question isn’t about my inability to understand that regression coefficients provide a neat...

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    What are your thoughts?

    Amy Perfors

    Ah, the beginning of fall term -- bringing with it the first anniversary of this blog (yay!), a return to our daily posting schedule (starting soon), and a question for you, our readers:

    Do you have any feedback for us? Specifically, are there topics, issues, or themes you would like us to cover more (or less) than we do? Would you like to see more discussion of specific content and papers? More posts on higher-level, recurring issues in each of our fields (or across fields)? More musings about teaching, academia, or the sociology of...

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    What determines which statistical software you use?

    I was recently involved in a discussion among fellow grad students about what determines which statistical software package people use to analyze their data. For example, this recent market survey lists 44 products selected from 31 vendors and they do not even include packages like R that many people around Harvard seem to use. Another survey conducted by Alan Zaslavsky lists 15 packages while `just’ looking at the available software for the...

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    What Did (and Do We Still) Learn from the La Londe Dataset (Part I)?

    Jens Hainmueller

    In a pioneering paper, Bob La Londe (1986) used experimental data from the National Supported Work Demonstration Program (NSW) as well as observational data from the Current Population Survey (CPS) and the Panel Study of Income Dynamics (PSID) to evaluate the reliability with which conventional estimators recover the experimental target estimate. He utilized the experimental data to establish a target estimate of the average treatment effect, then...

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    What Did (and Do We Still) Learn from the La Londe Dataset (Part II)?

    Jens Hainmueller

    I ended yesterday's post about the famous LaLonde dataset, with the following two questions: (1) What have we learned from the La Londe debate? (2) Does it makes sense to beat this dataset any further or have we essentially exhausted the information that can be extracted from this data and need to move one to new datasets?

    On the first point, VERY bluntly summarized, the comic strip history goes somewhat like this. First, La Londe showed that regression and IV do not get it right. Next, Heckman's research group released a string of papers in...

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    What is Japan doing at 2:04pm?

    You can now answer that question and so many more. The Japanese Statistics Bureau conducts a survey every five years called the "Survey on Time Use and Leisure Activities" where they give people journals to record their activities throughout the day. Thus, they have a survey of what people are in Japan at any given time of the day. This is fun data in of itself, but it was made downright addictive by Jonathan Soma who created a slick Stream Graph based on the data. (via...

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    What is the likelihood function?

    An interesting 1992 paper by Bayarri and DeGroot entitled “Difficulties and Ambiguities in the Definition of a Likelihood Function” (gated version) grapples with the problem of defining the likelihood when auxiliary variables are at hand. Here is the abstract:

    The likelihood function plays a very important role in the development of both the theory and practice of statistics. It is somewhat surprising to realize that no general rigorous definition of a likelihood...

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    Which Color for your Figure?

    ever wondered about what would be the best color for your graphs? While common in the sciences, it may be fair to say that the use of color in graphs is still under-appreciated in many social science fields. Colors can be a every effective tool to visualize data in many forms, because color is essentially a 3-d concept:

    - hue (red, green, blue)
    - value/lightness: (light vs. dark)
    - saturation/chroma (dull vs. vivid)

    From my limited understanding of this topic, not much scientific knowlegde exists about how color is best used. However, a few general principles...

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    What is P(Obama beats McCain)?

    While the Democratic nomination contest drags on (and on and on...; Tom Hanks declared himself bored with the race last week), attention is turning to hypothetical general election matchups between Hilary Clinton or Barack Obama and John McCain. Mystery Pollster has a post up reporting on state-by-state hypothetical matchup numbers obtained from surveys of 600 registered voters in each state conducted by ...

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    Who makes a good peer reviewer?

    Amy Perfors

    One of the interesting things about accruing more experience in a field is that as you do so, you find yourself called upon to be a peer reviewer more and more often (as I'm discovering). But because I've never been an editor, I've often wondered what this process looks like from that perspective: how do you pick reviewers? And what kind of people tend to be the best reviewers?

    A recent article in the (open-access) journal

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    Who Voted for the Nazis?

    While everyone is thinking about how the U.S. presidential election will turn out, I thought some of you might also be interested in a forthcoming Journal of Economic History article on a venerable electoral question -- why a democratic electorate in Germany chose a party which then ended their democracy. The article is "Ordinary Economic Voting Behavior in the Extraordinary Election of Adolf Hitler," by me, Ori Rosen,...

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    Why does repeated lying work?

    It's a common truism, familiar to most people by now thanks to advertising and politics, that repeating things makes them more believable -- regardless of whether they're true or not. In fact, even if they know at the time that the information is false, people will still be more likely to believe something the more they hear it. This phenomenon, sometimes called the reiteration effect, is well-studied and well-documented. Nevertheless, from a statistical learning point of view, it is extremely counter-intuitive: shouldn't halfway decent learners learn to discount...

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