http://qssi.psu.edu/ Quantitative Social Science Initiative (QuaSSI): Upcoming QuaSSI and Campus Events en-us qssi.psu.edu http://qssi.psu.edu/quaph.html Featuring talks by Jeffery Jenkins (Virginia), Benjamin Valentino (Dartmouth), and Daniel Ziblatt (Harvard). Lunch will be provided. http://qssi.psu.edu/newfaces.html http://qssi.psu.edu/seminars.html#wright A light lunch will be provided. http://qssi.psu.edu/seminars.html#luna A light lunch will be provided. http://qssi.psu.edu/seminars.html#chalasani Understanding causal relationships is central to understanding social phenomena. Yet, relatively few social scientists attempt to explicitly demonstrate causality in their work. In large part, this stems from the very nature of observational data such as surveys and censuses. Assignment of individuals to independent variables tends to be nonrandom, which then means that in a simple regression model, the explanatory variable indicating assignment to treatment will be correlated with the error term. Experimental data avert precisely this problem by randomizing assignment to treatment. However, experimental designs are often not feasible in the social sciences for a multitude of reasons. Matching methods such as the propensity score model use counterfactual reasoning and attempt to simulate an experiment using observational data. This talk will serve as an introduction to the motivations for using propensity scores, the fundamental logic of counterfactual models, and a step-by-step breakdown of how to implement a propensity score model. A light lunch will be provided. http://qssi.psu.edu/seminars.html#quinn What, if anything, should one infer about the causal effect of a binary treatment on a binary outcome from a 2×2 cross-tabulation of non-experimental data? Many researchers would answer "nothing" because of the likelihood of severe bias due to the lack of adjustment for key confounding variables. This paper shows that such a conclusion is unduly pessimistic. Because the complete data likelihood under arbitrary patterns of confounding factorizes in a particularly convenient way, it is possible to parameterize this general situation with four easily interpretable parameters. Subjective beliefs regarding these parameters are easily elicited and honest subjective statements of uncertainty about causal effects become possible. This paper also develops a novel graphical display we call the confounding plot that quickly and efficiently communicates all patterns of confounding that would leave a particular causal inference relatively unchanged. This simple graph is so easy to generate and so informative that there is no reason it should not be a part of every analysis that attempts to make causal inferences from a 2×2 table. A light lunch will be provided. http://qssi.psu.edu/seminars.html#salganik This talk is motivated by a puzzling aspect of contemporary cultural markets: successful cultural products, such as hit songs, bestselling books, and blockbuster movies, are orders of magnitude more successful than average; yet which particular songs, books, and movies will become the next "big thing" appears impossible to predict. Here we propose that both of these features, which appear to be contradictory at the collective level, can arise from the process of social influence at the individual level. To explore this possibility empirically we constructed a website where participants could listen to, rate, and download new music, and more importantly, where we could control the information that these participants had about the behavior of others. Using a novel experimental design we found support for our ideas in a series of four experiments involving a total of 27,267 participants. A light lunch will be provided. http://qssi.psu.edu/seminars.html#robinson Functional Magnetic Resonance Imaging (fMRI) is an imaging technique that indirectly measures brain activity by detecting blood oxygenation level dynamics that are believed to be the result of active neuronal communities. Since the early 1990's, fMRI has become one of most popular and powerful imaging techniques. fMRI has been utilized by several different fields, such as neuroscience, psychology, sociology, and medicine, and has been innovative in helping clinicians and researchers in diagnosing pathologies and understanding brain function in animals and humans. The workshop will focus on the basics involved in fMRI studies and include explanations regarding: 1) the biological response fMRI is based upon 2) basic components and physics of fMRI and equipment 3) fMRI designs and studies 4) fMRI data analysis 5) and fMRI study examples. A light lunch will be provided.