Social Science Statistics Blog

12 May 2012

From sketch to graphic

I just ran across chartsnthings (h/t to Gelman). Kevin Quealy at the New York Times graphics department shows the progression from initial sketch to final graphic.

Thoughts:

1) I love seeing other people's first sketches. I sketch first too, and I find that the quality of any graphic can mostly be determined by how good the idea was when I first sketched it.

2) This reminded me that rather than using R to make my final figures, I really need run them through Illustrator. Nathan Yau's book Visualize This gives some awesome worked examples of how to clean up R graphics in Illustrator. (And for Harvard folks, the book is available online through Widener library!).

Posted by Richard Nielsen at 10:58 PM | Comments (0)

23 April 2012

App Stats: Elwert on "Endogenous Selection"

We hope you can join us this Wednesday, April 25, 2012 for the final session of the Applied Statistics Workshop this semester. Felix Elwert, Assistant Professor from the Department of Sociology at the University of Wisconsin-Madison, will give a presentation entitled "Endogenous Selection". A light lunch will be served at 12 pm and the talk will begin at 12.15.

"Endogenous Selection"
Felix Elwert
Department of Sociology, University of Wisconsin-Madison
CGIS K354 (1737 Cambridge St.)
Wednesday, April 25th, 2012 12.00 pm

Abstract:

Selection bias is a central problem for causal inference in the social sciences. Quite how central a problem it is, however, is often obscured by ambiguous terminology, needlessly technical presentations, and narrow rules of thumb. This paper uses directed acyclic graphs (DAGs) to advance a precise yet intuitive global definition of endogenous selection bias and argue its theoretical and practical centrality for causal inference. The paper clarifies the fundamental structural difference between confounding and endogenous selection, shows that nearly all non-parametric identification problems relate to either confounding or endogenous selection, and argues that the problem of endogenous selection is indifferent to timing. Perhaps most importantly, we illustrate the importance of endogenous selection bias with numerous and varied examples from empirical social research.

This is joint work with Chris Winship.

Posted by Konstantin Kashin at 12:43 PM | Comments (0)

16 April 2012

App Stats: Wasow on "Violence and Voting: Did the 1960s Urban Riots Reshape American Politics?"

We hope you can join us this Wednesday, April 18, 2012 for the Applied Statistics Workshop. Omar Wasow, a Ph.D. candidate from the Department of Government and the Department of African and African American Studies at Harvard University, will give a presentation entitled "Violence and Voting: Did the 1960s Urban Riots Reshape American Politics?" A light lunch will be served at 12 pm and the talk will begin at 12.15.

"Violence and Voting: Did the 1960s Urban Riots Reshape American Politics?"
Omar Wasow
Government Department, Harvard University
CGIS K354 (1737 Cambridge St.)
Wednesday, April 18th, 2012 12.00 pm

Abstract:

Between 1964 and 1971, more than 750 riots flared up in black neighborhoods across the United States. Scholarship on how the American polity respond to these violent protests is contested. Some scholars argue that urban riots produced a conservative ``backlash'' among white voters, while other scholars find little or no effect. Using a measure that incorporates the location, timing and severity of urban riots between 1964 and 1971, I examine whether increased exposure to urban riots is associated with decreased support for the Democratic party. In the 1964, 1968 and 1972 presidential elections, I find a strong negative relationship between exposure to civil unrest and the county-level Democratic vote share. I find a similar negative relationship between exposure to riots and Democratic vote share in congressional elections between 1968 and 1972. Finally, I find that in counterfactual scenarios of fewer riots the Democratic presidential nominee, Hubert Humphrey, would have beaten the Republican nominee, Richard Nixon, in the 1968 election. As African Americans were strongly identified with the Democratic party in this time period, my results suggest that, in at least some contexts, political violence by a minority group may contribute to a backlash among segments of the mass electorate and encourage outcomes directly at odds with the preferences of the protestors.

Posted by Konstantin Kashin at 12:53 AM | Comments (0)

9 April 2012

App Stats: Glynn on "Using Post-Treatment Variables to Establish Upper Bounds on Causal Effects: Assessing Executive Selection Procedures in New Democracies"

We hope you can join us this Wednesday, April 11, 2012 for the Applied Statistics Workshop. Adam Glynn, Associate Professor from the Department of Government at Harvard University, will give a presentation entitled "Using Post-Treatment Variables to Establish Upper Bounds on Causal Effects: Assessing Executive Selection Procedures in New Democracies". A light lunch will be served at 12 pm and the talk will begin at 12.15.

"Using Post-Treatment Variables to Establish Upper Bounds on Causal Effects: Assessing Executive Selection Procedures in New Democracies"
Adam Glynn
Government Department, Harvard University
CGIS K354 (1737 Cambridge St.)
Wednesday, April 11th, 2012 12.00 pm

Abstract:

In this paper we propose an adjustment based on post-treatment variables for some standard estimators of the average treatment effect on the treated. Under relatively weak conditions, this adjusted estimator will provide an upper bound for the effect and in some cases lower bounds on p-values. Additionally, this approach does not place a restriction on the outcome variable and allows for multiple mechanisms by which the treatment has an effect on the outcome. We also demonstrate that this adjustment will reduce the estimated effect in a wide variety of circumstances, and therefore, when the assumptions for the adjusted estimator are preferable to the assumptions for the unadjusted estimator, the adjustment can be used as a robustness check. This method is illustrated with an assessment of the effects of using plurality rules for the first multi-party presidential elections in third wave of democracy in sub-Saharan Africa.

This is joint work with Nahomi Ichino.

Posted by Konstantin Kashin at 11:20 AM | Comments (1)

1 April 2012

App Stats: Bahar on "International Knowledge Diffusion and the Comparative Advantage of Nations"

We hope you can join us this Wednesday, April 4, 2012 for the Applied Statistics Workshop. Dany Bahar, a Ph.D. Candidate in Public Policy at the Harvard Kennedy School, will give a presentation entitled "International Knowledge Diffusion and the Comparative Advantage of Nations". A light lunch will be served at 12 pm and the talk will begin at 12.15.

"International Knowledge Diffusion and the Comparative Advantage of Nations"
Dany Bahar
Harvard Kennedy School
CGIS K354 (1737 Cambridge St.)
Wednesday, April 4th, 2012 12.00 pm

Abstract:

In this paper we document that the probability that a product is added to a country's export basket is, on average, 65% larger if a neighboring country is a successful exporter of that same product. We interpret our result as evidence of international intra-industry knowledge diffusion. Our results are consistent with the overall consensus in the literature on technology spillovers: diffusion is stronger at shorter distances; is weaker for more knowledge-intensive products; and has become faster over time.

This is joint work with Ricardo Hausmann and Cesar Hidalgo.

Posted by Konstantin Kashin at 11:44 PM | Comments (5)

26 March 2012

App Stats: Yamamoto on "A Multinomial Response Model for Varying Choice Sets, with Application to Partially Contested Multiparty Elections"

We hope you can join us this Wednesday, March 28, 2012 for the Applied Statistics Workshop. Teppei Yamamoto, Assistant Professor from the Department of Political Science at MIT, will give a presentation entitled "A Multinomial Response Model for Varying Choice Sets, with Application to Partially Contested Multiparty Elections". A light lunch will be served at 12 pm and the talk will begin at 12.15.

"A Multinomial Response Model for Varying Choice Sets, with Application to Partially Contested Multiparty Elections"
Teppei Yamamoto
Department of Political Science, MIT
CGIS K354 (1737 Cambridge St.)
Wednesday, March 28th, 2012 12.00 pm

Abstract:

This paper proposes a new multinomial choice model which explicitly takes into account variation in choice sets across observations. The proposed varying choice set logit model relaxes the independence of irrelevant alternatives assumption by allowing the individual random utility function to directly depend on choice set types, and can be applied to a variety of data in which some individuals can only choose from a subset of the theoretically possible responses. Both frequentist and Bayesian simulation-based estimation procedures are developed using the Monte Carlo expectation-maximization algorithm and Markov chain Monte Carlo, respectively. The proposed model can be used to analyze survey data in partially contested multiparty elections in which some political parties do not run their candidates in every district. For illustration, I apply the proposed method to the 1996 Japanese general election, where none of the districts was contested by all of the six major parties.

Posted by Konstantin Kashin at 1:20 AM | Comments (2)

19 March 2012

App Stats: Reshef on "Detecting Novel Bivariate Associations in Large Data Sets"

We hope you can join us this Wednesday, March 21, 2012 for the Applied Statistics Workshop. David Reshef, an MD/PhD student at the Harvard-MIT Division of Health Sciences and Technology (HST), will give a presentation entitled "Detecting Novel Bivariate Associations in Large Data Sets". A light lunch will be served at 12 pm and the talk will begin at 12.15.

"Detecting Novel Bivariate Associations in Large Data Sets"
David Reshef
Harvard-MIT Division of Health Sciences and Technology
CGIS K354 (1737 Cambridge St.)
Wednesday, March 21st, 2012 12.00 pm

Abstract:

Identifying interesting relationships between pairs of variables in large data sets is increasingly important. One way of doing so is to search such data sets for pairs of variables that are closely associated. This can be done by calculating some measure of dependence for each pair, ranking the pairs by their scores, and examining the top-scoring pairs. We outline two heuristic properties--generality and equitability--that the statistic we use to measure dependence should have in order for such a strategy to be effective. We present a measure of dependence for two-variable relationships, the maximal information coefficient (MIC), that has these properties. MIC captures a wide range of associations both functional and not (generality), and assigns similar scores to relationships with similar noise levels, regardless of relationship type (equitability). Finally, we show that MIC belongs to a larger class of maximal information-based nonparametric exploration (MINE) statistics for identifying and classifying relationships.

Posted by Konstantin Kashin at 12:35 AM | Comments (0)

6 March 2012

Rainfall: not such a great instrument after all...

Every discovery of a plausible instrumental variable sparks a cottage industry of papers all using the same instrument to ask different questions. A working paper by Heather Sarsons, titled "Rainfall and Conflict" calls one of these cottage industries into serious question. From the abstract:

Starting with Miguel, Satyanath, and Sergenti (2004), a large literature has used rainfall variation as an instrument to study the impacts of income shocks on civil war and conflict. These studies argue that in agriculturally-dependent regions, negative rain shocks lower income levels, which in turn incites violence. This identi…cation strategy relies on the assumption that rainfall shocks affect conflict only through their impacts on income. I evaluate this exclusion restriction by identifying districts that are downstream from dams in India. In downstream districts, income is much less sensitive to rainfall fluctuations. However, rain shocks remain equally strong predictors of riot incidence in these districts. These results suggest that rainfall affects rioting through a channel other than income and cast doubt on the conclusion that income shocks incite riots.

It's a short, readable paper -- worth checking out if you're into this kind of thing.

Posted by Richard Nielsen at 7:56 PM

5 March 2012

App Stats: Goodman on "Flaking Out: Snowfall, Disruptions of Instructional Time, and Student Achievement"

We hope you can join us this Wednesday, March 7, 2012 for the Applied Statistics Workshop. Joshua Goodman, Assistant Professor of Public Policy at the Harvard Kennedy School, will give a presentation entitled "Flaking Out: Snowfall, Disruptions of Instructional Time, and Student Achievement". A light lunch will be served at 12 pm and the talk will begin at 12.15.

"Flaking Out: Snowfall, Disruptions of Instructional Time, and Student Achievement"
Joshua Goodman
Harvard Kennedy School
CGIS K354 (1737 Cambridge St.)
Wednesday, March 7th, 2012 12.00 pm

Abstract:

Recent research on charter schools, summer learning loss, and international achievement suggests that instructional time is a critical input to the education production function. Using student and school-grade fixed effects models with data from Massachusetts, I find no relation between school closures and achievement but a strong relation between student absences and achievement. I then confirm these results using temporal and spatial variation in snowfall to provide better identification. Extreme snowfall induces school closures but does not affect achievement. Moderate snowfall induces student absences and does reduce achievement. Instrumental variables estimates suggest that each absence induced by bad weather reduces math achievement by 0.05 standard deviations. These results are consistent with a model of instruction in which coordination of students is the central challenge. Teachers deal well with coordinated disruptions of instructional time like school closures, but deal poorly with absences that affect different students and different times. These estimates suggest that absences are responsible for up to 20% of the achievement gap between poor and nonpoor students. They also suggest that policies designed solely to increase instructional time may not be effective.

Posted by Konstantin Kashin at 3:58 AM

27 February 2012

App Stats: Pfister on "Visual Computing in Biology"

We hope you can join us this Wednesday, February 29, 2012 for the Applied Statistics Workshop. Hanspeter Pfister, Gordon McKay Professor of Computer Science at the School of Engineering and Applied Sciences at Harvard University, will give a presentation entitled "Visual Computing in Biology". A light lunch will be served at 12 pm and the talk will begin at 12.15.

"Visual Computing in Biology"
Hanspeter Pfister
School of Engineering and Applied Sciences, Harvard University
CGIS K354 (1737 Cambridge St.)
Wednesday, February 29th, 2012 12.00 pm

Abstract:

Many areas in science are experiencing a flood of data arising in part from the development of instruments that acquire information on an unprecedented scale. This is particularly true in biology, where huge amounts of heterogeneous data are acquired from microarrays, scanners, microscopes, and various other instruments. Visual computing tools are essential to gain insights into this data by combining computational analysis with the power of the human perceptual and cognitive system and enabling data exploration through interactive visualizations. In this talk I will present some of my group's work in visual computing and give an overview of several successful visualization projects in the areas of genomics and systems biology. I then will focus on our work on visual computing in Connectomics, a new field in neuroscience that aims to apply biology and computer science to the grand challenge of determining the detailed neural circuitry of the brain.

Posted by Konstantin Kashin at 1:19 AM