Kat Hoffman

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Kat Hoffman

Kat Hoffman

@kat_hoffman_

@kathoffman.bsky.social biostatistician + PhD student @UWBiostat. learning + writing about better ways to conduct research. #rstats, #dataviz, causal inference

Seattle, WA Katılım Ocak 2018
652 Takip Edilen2.2K Takipçiler
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Kat Hoffman
Kat Hoffman@kat_hoffman_·
A tutorial on Longitudinal Modified Treatment Policies-- a flexible method for defining, identifying, and estimating causal parameters of interest-- is now in @EpidemiologyLWW! 🔗journals.lww.com/epidem/abstrac… cc🌟coauthors: @dasalazarb @nickWillyamz @kara_rudolph @ildiazm
Kat Hoffman@kat_hoffman_

updated tutorial on Longitudinal Modified Treatment Policies is now on arxiv! 🔗 arxiv.org/abs/2304.09460… for those at ACIC, i'll be hanging out by this poster today from 5-6:30pm and would love to chat about LMTPs, methodology tutorials, etc.

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Peter Hull
Peter Hull@instrumenthull·
Apropos of nothing, here is a problem set question from one of my undergrad econometrics courses
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Prof Lennart Nacke, PhD
Prof Lennart Nacke, PhD@acagamic·
What should you call your academic event? Another great flowchart from PhD Comics.
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Iván Díaz
Iván Díaz@ildiazm·
Our Division is hosting its inaugural yearly Biostatistics Symposium, and this year the topic is Causal Inference! We have an exciting lineup of speakers listed below. If you are in the NYC area, please join us! Link to register in the QR below.
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Michael Pyrcz🌻
Michael Pyrcz🌻@GeostatsGuy·
Many of my students struggle with the distinction between Ordinary Least Squares (OLS) and Maximum Likelihood Estimation (MLE). To clarify, we use an interactive #Python dashboard that fits parameters to a Gaussian distribution based on a given dataset. This visual approach helps them see the difference: OLS minimizes the mismatch between the model and the data, while MLE maximizes the likelihood of the data given the model parameters. With this tool, the concepts become much clearer! I share it on #GitHub @ github.com/GeostatsGuy/Da… ∀. #DataScience #MachineLearning
GIF
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Anjalie Field
Anjalie Field@anjalie_f·
As application season rolls around again, here's your reminder that materials from my successful applications are available on my website (NSF-GRFP, Google PhD Fellowship, Stanford data science postdoc, and CS faculty job search): anjalief.github.io/statements.html
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Kat Hoffman
Kat Hoffman@kat_hoffman_·
amazing resource for PhD applicants by @drlucylai below! tag-teaming off her with my own post on my Biostatistics PhD application experience (applied Fall '22) ⤵️ khstats.com/blog/phd-apps/
Lucy Lai, PhD@drlucylai

✨it's PhD application season again!✨ i am re-sharing my popular guide on applying for PhD programs in STEM, that has now been viewed 60k+ times over the past 6 years😍 please RT and share with anyone that might find it useful! lucylai.com/blog/gradapps

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Crystal Lewis @cghlewis.bsky.social
Crystal Lewis @cghlewis.bsky.social@Cghlewis·
I can't remember the last time I renamed variables manually in #rstats. I always use my data dictionary for renaming! That way, if I ever need to update names in the future, I'm only updating once in my data dictionary, not in both my data dictionary and script. 🙌
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UW Biostatistics
UW Biostatistics@UWBiostat·
We’re seeking a new chair to lead a dedicated team of faculty, staff, and students who are passionate about developing and using rigorous quantitative methods to improve the well-being of communities in the United States and around the world. bit.ly/3MmZHwE
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Kat Hoffman
Kat Hoffman@kat_hoffman_·
Thank you to @AmstatNews for the support, and so many mentors for guidance/encouragement. Extra thanks to @ildiazm for helping me start methods research pre-PhD. Looking forward to year 2 at @UWBiostat!!
UW Biostatistics@UWBiostat

Congrats to @uwbiostat PhD student Kat Hoffman who has received the Gertrude M. Cox Scholarship. The award recognizes Hoffman’s methodological research developing machine-learning based methods drawing on causal inference on longitudinal interventions. bit.ly/4fHQOv8

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Anthony Bonato
Anthony Bonato@Anthony_Bonato·
More proof techniques
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Kat Hoffman
Kat Hoffman@kat_hoffman_·
A tutorial on Longitudinal Modified Treatment Policies-- a flexible method for defining, identifying, and estimating causal parameters of interest-- is now in @EpidemiologyLWW! 🔗journals.lww.com/epidem/abstrac… cc🌟coauthors: @dasalazarb @nickWillyamz @kara_rudolph @ildiazm
Kat Hoffman@kat_hoffman_

updated tutorial on Longitudinal Modified Treatment Policies is now on arxiv! 🔗 arxiv.org/abs/2304.09460… for those at ACIC, i'll be hanging out by this poster today from 5-6:30pm and would love to chat about LMTPs, methodology tutorials, etc.

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Josh Weinstock
Josh Weinstock@josh_weinstock·
Thrilled to share that I am joining the Department of Human Genetics @EmoryMedicine as an Assistant Professor! I was an undergraduate at Emory before, and it's an honor and a privilege to return as faculty. (1/3)
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Kat Hoffman
Kat Hoffman@kat_hoffman_·
thank you @BhramarBioStat for years of encouragement, going all the way back to when I was an undergrad-- giving me an invitation to attend summer BDSI talks as soon as you learned I lived locally 💛💙 Michigan will miss you!
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Kat Hoffman
Kat Hoffman@kat_hoffman_·
@guhbao theres definitely some overlap in the R packages {lmtp} and {ltmle}! here's some diffs: - lmtp can be used for MTP estimands (intervening on natural value of treatment) - lmtp encodes an additional estimator (SDR) for static/dynamic/MTPs - lmtp does not encode MSMs
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Kat Hoffman
Kat Hoffman@kat_hoffman_·
updated tutorial on Longitudinal Modified Treatment Policies is now on arxiv! 🔗 arxiv.org/abs/2304.09460… for those at ACIC, i'll be hanging out by this poster today from 5-6:30pm and would love to chat about LMTPs, methodology tutorials, etc.
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Kat Hoffman@kat_hoffman_

new tutorial paper! 🤩 check it out if you're looking to add a general causal inference method to your toolbox. 🧰 LMTP + #rstats pkg {lmtp} is especially useful for time-varying data and/or continuous exposures. 🔗 : arxiv.org/pdf/2304.09460… pre-print highlights ⬇️ 1/n

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Kat Hoffman
Kat Hoffman@kat_hoffman_·
@ibddoctor yeah! you could consider estimands involving interventions where you modify the natural value of treatment dose at some or all of your 8 week intervals (e.g. decrease by X% or X units, or decrease from ordinal categories e.g. high dose to medium dose, medium dose to low dose)
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Peter Higgins
Peter Higgins@ibddoctor·
@kat_hoffman_ Could this work for a dose-titration study (opportunity to dose-change every 8 weeks)?
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Keşfet

@UWBiostat @UWStat @drlucylai @AmstatNews @ildiazm @EpidemiologyLWW @dasalazarb @kara_rudolph