Mary Beth Landrum Profile
Mary Beth Landrum

@Mblandrum

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244
Following
541
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66

Joined March 2012
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@haaretzcom
Haaretz.com
9 months
"I called myself Haredi even when I was secular": "Shtisel" creator on new spin-off show "Kugel" / @AdrianHennigan1 https://t.co/Osx6Gj1z8r
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haaretz.com
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@Mblandrum
Mary Beth Landrum
1 year
Agree -- such important work! Congrats Lindsay!
@nolankavanagh
Nolan M. Kavanagh
1 year
@LindsayOverhage congratulations, Lindsay!!! it’s great to see this out and at such a great journal.
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@nolankavanagh
Nolan M. Kavanagh
1 year
@LindsayOverhage congratulations, Lindsay!!! it’s great to see this out and at such a great journal.
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@Mblandrum
Mary Beth Landrum
3 years
Damn that was fun! ⁦@Cutler_econ
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@BillKristol
Bill Kristol
3 years
"Mr. Mehlhorn shared a similar rationale for supporting Ms. Cheney. 'If that is the dividing line—if you’re for the peaceful transfer of power or not—you rally around Liz Cheney, who is making it the most important issue personally.'” https://t.co/md2aZ9ltOP
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nytimes.com
Despite policy disagreements, donors like Jeffrey Katzenberg are backing the Wyoming Republican because of her role on the House committee investigating the Jan. 6 attack.
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@Mblandrum
Mary Beth Landrum
5 years
Congrats! I love this work, can't wait to read the paper.
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@Mblandrum
Mary Beth Landrum
5 years
Thanks for sharing
@EKTBenn
Emma Benn
5 years
This piece is a #MustRead by @WeRepSTEM. I can completely relate as a Black Biostatistics Professor. Please read this Dept. chairs, STEM program directors & faculty, institutional leaders, etc. who have recently been reiterating to us their renewed commitment to diversity. ✊🏾✊🏾✊🏾
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@Mblandrum
Mary Beth Landrum
6 years
We've been looking for a couple of weeks. David has contacts. Not a lot of dogs available right now, sadly.
@petelyu
Peter Lyu
6 years
Wife and I are thinking about adopting a dog from the eastern Mass area. Where should we start looking?
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@Mblandrum
Mary Beth Landrum
6 years
Yes -- I believe it's not just Cox models, but all non-linear models (including logistic). Another argument for linear probability models -- at least if the ATE is your desired estimand. I might loose my biostat degree over this comment.
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@Mblandrum
Mary Beth Landrum
6 years
Really enjoyed your presentation of this work. Can't wait to read the paper (and all the weedy details). Congrats!
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@Mblandrum
Mary Beth Landrum
6 years
My daughter Kate is the best
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@Mblandrum
Mary Beth Landrum
7 years
Did you explain the missing corner?
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@Mblandrum
Mary Beth Landrum
7 years
Turkeys?
@AnupamBJena
Anupam Jena
7 years
@LeemoreDafny @Cutler_econ I am curious what David was looking at outside of the window...cc @Mblandrum
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@Mblandrum
Mary Beth Landrum
7 years
Exactly. High performers could get a pass for some number of years (or perhaps be subject to random selection for measurement, etc.). Lots of room to improve the value of quality measurement.
@benharder
Ben Harder #BlackLivesMatter
7 years
Very intriguing, @Mblandrum. Would you suggest, then, that high-performing hospitals—(pick any reasonable definition: CMS 5-star, VBP bonus-receiving, U.S. News-ranked, etc.)—might not need to be subjected to the full burden of current reporting requirements for reaccreditation?
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@besttrousers
Matt Darling 🌐🏗️
7 years
@dynarski <starts writing a paper about the cog. biases that result in someone answering #2, when, by definition, the "best boy EVER" is, necessarily, "SUCH a good boy.">
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@RogueOfSports
Rogue
7 years
@UMichFootball Defense is really hurting. Shea. We need you.
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@hannahdreier
Hannah Dreier
7 years
When the gang MS-13 started killing immigrant kids in the woods of Long Island, police dismissed the attacks as "misdemeanor murder" and listed the victims as runaways. Families had to use taxi drivers as interpreters, and search for the bodies themselves.
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features.propublica.org
Police on Long Island wrote off missing immigrant teens as runaways. One mother knew better — and searched MS-13’s killing fields for answers.
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@Mblandrum
Mary Beth Landrum
7 years
Love this THREAD
@jamie_daw
Jamie Daw
7 years
THREAD @laura_tastic summarizes some of the lessons we’ve learned since taking a closer look at matching in diff-in-diff. Overall lesson: be careful and think about the data generating/tx assignment process behind your data
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