Daniel Scharfstein

327 posts

Daniel Scharfstein

Daniel Scharfstein

@dscharf3

Professor of Biostatistics, Department of Population Health Sciences, University of Utah School of Medicine

Salt Lake City, UT Katılım Mayıs 2012
218 Takip Edilen590 Takipçiler
Daniel Scharfstein retweetledi
U of U Biostatistics
U of U Biostatistics@UofUBiostats·
We're representing #biostatselevated at #OneU @UofUDELPHI Data Science Symposium today 🌟 Talks by @UofUPHS faculty Dr. Jincheng Shen and PhD student Julia Bohman & with posters by PhD students Hoajia Li, Sima Najafzadeh & affiliated faculty Dr. Yue Zhang.
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Daniel Scharfstein retweetledi
U of U Biostatistics
U of U Biostatistics@UofUBiostats·
#Biostatistics Faculty applications accepted until November 15! Collaborate with brilliant minds in a supportive environment, all while enjoying world-class recreation nearby. More info at bit.ly/JobsPHS #biostatselevated @UofUHealth @UofUResearch @UofUMedicine
U of U Biostatistics@UofUBiostats

We're hiring! Seeking #biostatistics faculty, post doctoral fellows, and PhD Students to join our amazing division in #beUTAHful Salt Lake City. More info at bit.ly/JobsPHS. #biostatselevated #academics #postdocjobs #facultyjobs #phd #biostats @UofUMedicine @UofUHealth

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U of U PHS
U of U PHS@UofUPHS·
Congratulations to Dr. @adambress on being named a 2024 Presidential Scholar at the U! 🎉 Recipients of this award are chosen for their leadership in their field & significant contribution to scholarship, education & outreach at @UUtah. Read more @ bit.ly/APB1024
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Daniel Scharfstein retweetledi
Covariate Adjustment ASA BIOP Working Group
Our next journal club is Oct 11 at 11 am EST (This Friday). The speaker is our own member, Jonathan Chipman, from Utah University. Zoom link: umich.zoom.us/j/7573650566 Title: Covariate-Adjusted Randomization Analyzed with Randomization-Based Inference
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Iván Díaz
Iván Díaz@ildiazm·
@ADAlthousePhD @Lach_cribb It has certainly helped applied researchers do better research, but as it gains popularity it is being used to refer to studies that suffer from the very issues it was supposed to address.
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Daniel Scharfstein
Daniel Scharfstein@dscharf3·
@ildiazm I am not as familiar with the history of science as you. Can you point me to the many tools for falsifiability beyond experiments? Also, I think it may be a block of salt not just a grain.
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Iván Díaz
Iván Díaz@ildiazm·
That is OK in my mind, it just means that claims from an analysis that is not immediately falsifiable by experiment should be taken with an extra grain of salt. Note that science has many tools for falsifiability beyond experiments. /end
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Iván Díaz
Iván Díaz@ildiazm·
My original post goes beyond mediation analysis, but let me respond to this particular issue in the case of mediation analysis in a little thread: 🧵
Daniel Scharfstein@dscharf3

@ildiazm I have always been uncomfortable with natural direct and indirect effects and the assumptions required for identification. Can you explain how you think about these from your nature viewpoint?

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Daniel Scharfstein
Daniel Scharfstein@dscharf3·
@ildiazm Why should I believe that this model represents reality somewhat accurately? Should mediation papers that report natural direct and indirect effects discuss the reality of this model?
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Iván Díaz
Iván Díaz@ildiazm·
For (1), let the causal model be A->M->Y with an NPSEM A=h(U), M=f(A,V), and Y=g(A,M,E), (U,V,E) are unmeasured. If you believe this model represents reality somewhat accurately, you can then decide to analyze how the function composition g(a1, f(a2, V), E) varies with (a1, a2).
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Daniel Scharfstein
Daniel Scharfstein@dscharf3·
@ildiazm I have always been uncomfortable with natural direct and indirect effects and the assumptions required for identification. Can you explain how you think about these from your nature viewpoint?
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Iván Díaz
Iván Díaz@ildiazm·
I still find it unbelievable that one day someone decided that causation was tied to human action (no causation without manipulation) instead of it just being a property of nature, and that most current debates in the field trace back to this misconception.
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Daniel Scharfstein
Daniel Scharfstein@dscharf3·
Excited to share my latest paper with @amoafo_linda and Elizabeth Platz; it develops a sensitivity analysis tool for evaluating the influence of unmeasured confounding in observational studies with time-to-event outcomes arxiv.org/abs/2403.02539
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