gov3009-l November 2021

gov3009-l@lists.fas.harvard.edu

2 participants
4 discussions

Gov 3009 Applied Statistics Workshop (12/1) -- Susan Murphy

by Shin, Sooahn

Dear Applied Statistics Workshop Community, Our next meeting of the semester will be at 12:10 pm (EST) Wednesday, December 1, where Susan Murphy<http://people.seas.harvard.edu/~samurphy/> (Harvard University) presents "Assessing Personalization in Digital Health." Abstract Reinforcement Learning provides an attractive suite of online learning methods for personalizing interventions in a Digital Health. However after an reinforcement learning algorithm has been run in a clinical study, how do we assess whether personalization occurred? We might find users for whom it appears that the algorithm has indeed learned in which contexts the user is more responsive to a particular intervention. But could this have happened completely by chance? We discuss some first approaches to addressing these questions. Where: CGIS Knafel Building, Room K354 (See this link<https://map.harvard.edu/?bld=04471&level=9> for directions). When: Wednesday, December 1 at 12:10 - 1:30 pm. (Bagged lunches available for pick-up at CGIS K354 11:30 - 11:45 am, for the participants who responded to our previous survey. The CGIS cafe on the first floor has been designated as an eating area, and participants may also use outdoor spaces for lunch. Please be present at K354 by 12:10 pm for the presentations.) Zoom link: https://harvard.zoom.us/j/97004196610?pwd=eGFydkF5RDRjUlk5RVcyTjV6OStUQT09 (For the participants who cannot join the session physically.) Schedule of the workshop: https://projects.iq.harvard.edu/applied.stats.workshop-gov3009 Looking forward to seeing you all on Wednesday! Best, Sooahn

2 years, 4 months

Gov 3009 Applied Statistics Workshop (11/17) -- Xiang Zhou

by Shin, Sooahn

Dear Applied Statistics Workshop Community, Our next meeting of the semester will be at *12:10 pm (EST) Wednesday, November 17*, where Xiang Zhou <https://scholar.harvard.edu/xzhou/home> (Harvard University) presents "Higher Education and the Black-White Earnings Gap." *Abstract* Higher education can be a double-edged sword in shaping the black-white earnings gap. It may serve as an equalizer, if black youth benefit more from attending and completing college than white youth. It may also reinforce racial inequality, given that black college-goers are less likely to complete college relative to white students. We employ a novel causal decomposition and a debiased machine learning method to isolate the equalizing and disequalizing effects of college and unveil the sources of these effects. Analyzing data from the NLSY97, we find that among men, a BA degree has a strong equalizing effect on earnings, but this equalizing effect is blunted by a disequalizing effect associated with unequal likelihoods of BA completion. Moreover, a BA degree narrows the male black-white earnings gap not by reducing the influence of class background and pre-college academic ability, but by lessening the “unexplained” penalty of being black in the labor market. To illuminate the policy implications of our findings, we estimate counterfactual earnings gaps under a series of idealized educational interventions. We find that interventions that both boost college attendance and BA completion rates and close racial disparities in these transitions can substantially reduce the black-white earnings gap. *Where:* CGIS Knafel Building, Room K354 (See this link <https://map.harvard.edu/?bld=04471&level=9> for directions). *When:* Wednesday, November 17 at 12:10 - 1:30 pm. (Bagged lunches available for pick-up at CGIS K354 *11:30 - 11:45 am*, for the participants who responded to our previous survey. The CGIS cafe on the first floor has been designated as an eating area, and participants may also use outdoor spaces for lunch. Please be present at K354 by 12:10 pm for the presentations.) *Zoom link*: https://harvard.zoom.us/j/97004196610?pwd=eGFydkF5RDRjUlk5RVcyTjV6OStUQT09 (For the participants who cannot join the session physically.) *Schedule of the workshop*: https://projects.iq.harvard.edu/applied.stats.workshop-gov3009 Looking forward to seeing you all on Wednesday! Best, Sooahn

2 years, 5 months

Gov 3009 Applied Statistics Workshop (11/10) -- Isaiah Andrews

by Shin, Sooahn

Dear Applied Statistics Workshop Community, Our next meeting of the semester will be at *12:10 pm (EST) Wednesday, November 10*, where Isaiah Andrews <https://projects.iq.harvard.edu/applied.stats.workshop-gov3009> (Harvard University) presents "Inference on Winners." This is joint work with Toru Kitagawa (University College London) and Adam McCloskey (University of Colorado). Please find the paper from this link <https://scholar.harvard.edu/files/iandrews/files/inference_on_winners.pdf>. *Abstract* Many empirical questions concern target parameters selected through optimization. For example, researchers may be interested in the effectiveness of the best policy found in a randomized trial, or the best-performing investment strategy based on historical data. Such settings give rise to a winner’s curse, where conventional estimates are biased and conventional confidence intervals are unreliable. This paper develops optimal confidence intervals and median-unbiased estimators that are valid conditional on the target selected and so overcome this winner’s curse. If one requires validity only on average over targets that might have been selected, we develop hybrid procedures that combine conditional and projection confidence intervals to offer further performance gains relative to existing alternatives. *Where:* CGIS Knafel Building, Room K354 (See this link <https://map.harvard.edu/?bld=04471&level=9> for directions). *When:* Wednesday, November 10 at 12:10 - 1:30 pm. (Bagged lunches available for pick-up at CGIS K354 *11:30 - 11:45 am*, for the participants who responded to our previous survey. The CGIS cafe on the first floor has been designated as an eating area, and participants may also use outdoor spaces for lunch. Please be present at K354 by 12:10 pm for the presentations.) *Zoom link*: https://harvard.zoom.us/j/97004196610?pwd=eGFydkF5RDRjUlk5RVcyTjV6OStUQT09 (For the participants who cannot join the session physically.) *Schedule of the workshop*: https://projects.iq.harvard.edu/applied.stats.workshop-gov3009 Looking forward to seeing you all on Wednesday! Best, Sooahn

2 years, 5 months

Gov 3009 Applied Statistics Workshop (11/3) -- James Robins

by Shin, Sooahn

Dear Applied Statistics Workshop Community, Our next meeting of the semester will be at *12:10 pm (EST) Wednesday, November 3*, where James Robins <https://www.hsph.harvard.edu/james-robins/> (Harvard University) presents "Target Trials: Emulating RCTs using Observational Longitudinal Data." *Abstract* Target trials are RCTs one would like to conduct but cannot for ethical, financial, and/or logistical reasons. As a consequence, we must emulate such trials from observational data. A novel aspect of target trial methodology is that, for purposes of data analysis, each subject in the observational study is ‘enrolled’ in all target trials for which the subject is eligible, instead of a single trial. I will compare the strengths and weakness of the target trial approach with alternative methods for estimation of causal effects from longitudinal data with time varying confounders: structural nested models, dynamic marginal structural models, and history adjusted marginal structural models. Finally, through empirical examples, I will examine the over-arching question: Are these methodologies sufficiently reliable for their substantive results to guide clinical practice. *Where:* CGIS Knafel Building, Room K354 (See this link <https://map.harvard.edu/?bld=04471&level=9> for directions). *When:* Wednesday, November 3 at 12:10 - 1:30 pm. (Bagged lunches available for pick-up at CGIS K354 *11:30 - 11:45 am*, for the participants who responded to our previous survey. The CGIS cafe on the first floor has been designated as an eating area, and participants may also use outdoor spaces for lunch. Please be present at K354 by 12:10 pm for the presentations.) *Zoom link*: https://harvard.zoom.us/j/97004196610?pwd=eGFydkF5RDRjUlk5RVcyTjV6OStUQT09 (For the participants who cannot join the session physically.) *Schedule of the workshop*: https://projects.iq.harvard.edu/applied.stats.workshop-gov3009 Looking forward to seeing you all on Wednesday! Best, Sooahn

2 years, 5 months

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gov3009-l November 2021