In 2004, Christakis and colleagues published findings that he and others used to argue for a link between early childhood television exposure and later attention problems, a claim that continues to be frequently promoted by the popular media. Using the same National Longitudinal Survey of Youth 1979 data set (N = 2,108), we conducted two multiverse analyses to examine whether the finding reported by Christakis and colleagues was robust to different analytic choices. We evaluated 848 models, including logistic regression models, linear regression models, and two forms of propensity-score analysis. If the claim were true, we would expect most of the justifiable analyses to produce significant results in the predicted direction. However, only 166 models (19.6%) yielded a statistically significant relationship, and most of these employed questionable analytic choices. We concluded that these data do not provide compelling evidence of a harmful effect of TV exposure on attention.

As robustness of social science is getting more attention, analytical choices have been found to be more important than previously thought. This thesis investigates robustness of intergenerational educational mobility estimates using multiverse analysis, a technique for incorporating many analyses into one framework while varying analytical choices such as variable coding, mobility measures, and exclusion criteria. Using ESS data from 16 European countries over nine survey rounds, results show substantial variation in point estimates, which in turn creates high variation in rankings of European countries. The conclusion is that analytical choices play an important role in calculating educational mobility estimates, and that ranking of European countries according to intergenerational mobility estimates is sensitive to varying these choices. Future mobility research should take this into account.