gov3009-l October 2020

gov3009-l@lists.fas.harvard.edu

1 participants
5 discussions

Fwd: Cancellation: Opportunity Insights Lunch and IQSS Joint talk Wednesday, October 28th at 12 noon (EST)

by Yamauchi, Soichiro

Hi all, Unfortunately, today's seminar is canceled. Instead, we will have an informal session on the regular zoom link: https://harvard.zoom.us/j/99424949004?pwd=aWtPNFM3ZzFYbWxIMXNoZDlyUElVZz09 Best, Soichiro ---------- Forwarded message --------- From: Thach, Elizabeth <elizabeth_thach(a)fas.harvard.edu> Date: Wed, Oct 28, 2020 at 10:37 AM Subject: Cancellation: Opportunity Insights Lunch and IQSS Joint talk Wednesday, October 28th at 12 noon (EST) To: Good morning, Unfortunately, due to unavoidable circumstances, today’s join lunch session with the IQSS is cancelled. Please join us for the next OI lunch on *November 11*, when Douglas Staiger (Dartmouth College), Sean Reardon (Stanford University), and Thomas J. Kane (Harvard) are presenting. Please see the attached revised schedule which reflects all changes to the semester’s schedule, namely that there is no lecture on Nov. 4. Rediet Abebe will be speaking in the spring. Please let me know if you have any questions. Best, Liz Elizabeth Thach Executive Assistant (p) 617-496-5409 elizabeth_thach(a)fas.harvard.edu *My pronouns are: she, her, hers* [image: tiny logo]

3 years, 6 months

Gov 3009 Applied Statistics Workshop (10/28) -- Fabian Pfeffer

by Yamauchi, Soichiro

Hi all, Our next virtual meeting will Wednesday, October 28, where we will hear Fabian Pfeffer (University of Michigan) presents research on "The Effects of Social Mobility on Individuals". This is a joint session with Opportunity Insights, and the seminar is scheduled from noon to 1pm (EDT). *Zoom Link (different from the usual link)*: https://harvard.zoom.us/j/92029171055?pwd=VzZLTUgzWGU3Skl0Wm9yRUVPcGNjUT09 Password: economics Schedule of the workshop: https://projects.iq.harvard.edu/applied.stats.workshop-gov3009 Best, Soichiro -- Soichiro Yamauchi PhD candidate Harvard University URL: https://soichiroy.github.io/

3 years, 6 months

Gov 3009 Applied Statistics Workshop (10/21) -- Eric Tchetgen Tchetgen

by Yamauchi, Soichiro

Hi all, Our next virtual meeting will be Wednesday, October 21, where we will hear Eric Tchetgen Tchetgen presents research on "An Introduction to Proximal Causal Learning". *Abstract*: A standard assumption for causal inference from observational data is that one has measured a sufficiently rich set of covariates to ensure that within covariates strata, subjects are exchangeable across observed treatment values. Skepticism about the exchangeability assumption in observational studies is often warranted because it hinges on one's ability to accurately measure covariates capturing all potential sources of confounding. Realistically, confounding mechanisms can rarely if ever, be learned with certainty from measured covariates. One can therefore only ever hope that covariate measurements are at best proxies of true underlying confounding mechanisms operating in an observational study, thus invalidating causal claims made on basis of standard exchangeability conditions. Causal learning from proxies is a challenging inverse problem which has to date remained unresolved. In this paper, we introduce a formal potential outcome framework for proximal causal learning, which while explicitly acknowledging covariate measurements as imperfect proxies of confounding mechanisms, offers an opportunity to learn about causal effects in settings where exchangeability on the basis of measured covariates fails. Sufficient conditions for nonparametric identification are given, leading to the proximal g-formula and corresponding proximal g-computation algorithm for estimation, both generalizations of Robins' foundational g-formula and g-computation algorithm, which account explicitly for bias due to unmeasured confounding. Both point treatment and time-varying treatment settings are considered, and an application of proximal g-computation of causal effects is given for illustration. *Link to paper*: https://arxiv.org/abs/2009.10982 *Zoom link*: https://harvard.zoom.us/j/99424949004?pwd=aWtPNFM3ZzFYbWxIMXNoZDlyUElVZz09 *Schedule of the workshop*: https://projects.iq.harvard.edu/applied.stats.workshop-gov3009 Best, Soichiro -- Soichiro Yamauchi PhD candidate Harvard University URL: https://soichiroy.github.io/

3 years, 6 months

Gov 3009 Applied Statistics Workshop (10/14) -- Luke Miratrix

by Yamauchi, Soichiro

Hi all, Our next virtual meeting will be Wednesday, October 14, where we will hear Luke Miratrix (Harvard University) presents research on "A Practitioner’s Guide to Intent-to-Treat Effects from Multisite (blocked) Individually Randomized Trials: Estimands, Estimators, and Estimates". *Abstract*: There are many ways to estimate an overall average effect of a large-scale multisite individually randomized control trial. The researcher can target the average effect across individuals or sites. Furthermore, the researcher can target the effect for the experimental sample or a larger population. If treatment effects vary across sites, these estimands can differ. Once an estimand is selected, an estimator must be chosen. Standard estimators, such as fixed-effects regression, can be biased. We describe 15 different estimators commonly in use, consider which estimands they are appropriate for, and discuss their properties in the face of cross-site effect heterogeneity. Using data from 12 large multisite RCTs, we estimate the effect (and standard error) using each estimator and compare the results. We assess the extent that these decisions matter in practice and provide guidance for applied researchers. Zoom link: https://harvard.zoom.us/j/99424949004?pwd=aWtPNFM3ZzFYbWxIMXNoZDlyUElVZz09 Schedule of the workshop: https://projects.iq.harvard.edu/applied.stats.workshop-gov3009 Best, Soichiro -- Soichiro Yamauchi PhD candidate Harvard University URL: https://soichiroy.github.io/

3 years, 6 months

Gov 3009 Applied Statistics Workshop (10/7) -- Felix Elwert

by Yamauchi, Soichiro

Hi all, Our next virtual meeting will be Wednesday, October 7, where we will hear Felix Elwer (University of Wisconsin-Madison) presents research on "Neighborhood Effects in Time." This talk is a joint session with Opportunity Insights and the talk will not be recorded. A* different zoom link* will be used for this week: https://harvard.zoom.us/j/92029171055?pwd=VzZLTUgzWGU3Skl0Wm9yRUVPcGNjUT09 Password: economics Best, Soichiro Yamauchi -- Soichiro Yamauchi PhD candidate Harvard University URL: https://soichiroy.github.io/

3 years, 6 months

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gov3009-l October 2020