Frank Harrell

@f2harrell · Nashville, TN · joined 16 Jan 2017

Biostatistician/Professor/Consultant/Founding Chair of Biostat, Vanderbilt U. Blog: Statistical Thinking:https://t.co/2BTEONzsfX @f2harrell on https://t.co/bsPN9JQNOS

30 378Followers

175Following

19 767Posts total

120.5KViews on collected posts

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Frank Harrell@f2harrell29 Aug

Any new field that comes on the scene quickly can vanish just as quickly. Witness data science, personalized medicine, precision medicine, many 'omics, and hopefully digital twins. 19.8K views · 128 likes · 18 reposts · 13 replies Open on X →

Frank Harrell@f2harrell23 Aug

@f2harrell @typstapp Texlive takes 9gb because you installed literally everything in the universe — from hyphenation patterns and fonts for languages you do not know exist to style files to draw the simpsons characters. You are making a rather idiotic comparison. 3K views · 36 likes · 2 reposts · 1 replies Open on X →

Frank Harrell@f2harrell23 Aug

@f2harrell @typstapp The bulk, the slowness, and the ugliness of (La)TeX piss me off. It's 2026. Why does compiling a scientific document take 8 seconds and result often in impossible-to-debug errors? TeX was a beautiful piece of software in 1978. Time to move on. 8.8K views · 49 likes · 3 reposts · 6 replies Open on X →

Frank Harrell@f2harrell23 Aug

@f2harrell @typstapp Can’t believe i get to say this to Harrell (whose work i use quite often) but: skill issue :) LaTeX does not need to use anywhere near as much space! 3.1K views · 19 likes · 1 reposts · 0 replies Open on X →

Frank Harrell@f2harrell23 Aug

The gold standard for producing PDF documents (especially books and journal articles) has been LaTeX. @typstapp re-engineered the entire process in an incredibly elegant extensible way. On my MacOS LaTeX (TexLive) takes 9.1GB of disk space. Typst takes 43MB. Not a misprint. 61.1K views · 523 likes · 22 reposts · 17 replies Open on X →

Frank Harrell@f2harrell20 Aug

The more I use @typstapp for producing pdf files (haven't gotten much into html production yet) the more I love it. I'm finishing, with Claude's help, major updates to the #rstats Hmisc and rms packages that add full Typst support. https://t.co/DvTXE5KCeB

5.5K views · 50 likes · 8 reposts · 3 replies Open on X →

Frank Harrell@f2harrell10 Aug

I appreciate @BaimInstitute making this video available. This was fun, and I hope the talk's content will stimulate others to think about how such approaches can make trials more efficient and will stimulate further discussion. There's plenty of controversy to go around. 4.4K views · 39 likes · 2 reposts · 1 replies Open on X →

Frank Harrell@f2harrell10 Aug

The recording from Baim Grand Rounds with @f2harrell on "Modernizing Clinical Trial Design and Analysis to Improve Efficiency & Flexibility" is now available on the Baim website. You can find it here: https://t.co/7m1EAr2Dxp https://t.co/ts66pzssLB

9.6K views · 40 likes · 13 reposts · 0 replies Open on X →

Frank Harrell@f2harrell10 Aug

Is it worthwhile to parametrically fit a distribution? Or better to just go with the empirical cumulative distribution function (ECDF) and its generalization - cumulative probability ordinal regression? New article: https://t.co/gVQtYsXkDU #Statistics 5.3K views · 75 likes · 14 reposts · 2 replies Open on X →

เทียบกับบัญชีขนาดเดียวกัน

9 โพสต์จาก 90 วันที่ผ่านมา เทียบกับช่วง 10K–100K ผู้ติดตาม แสดงในวงกว้าง แต่มีผู้ชมตอบสนองน้อย.

ยอดดูมัธยฐาน5 468บัญชีนี้937ค่ามัธยฐานของ 10K–100K

การเข้าถึง, %18.00%บัญชีนี้3.44%ค่ามัธยฐานของ 10K–100K

การมีส่วนร่วม, %0.93%บัญชีนี้1.55%ค่ามัธยฐานของ 10K–100K

ตัวชี้วัด	บัญชีนี้	ค่ามัธยฐานของ 10K–100K	อัตราส่วน
ยอดดูมัธยฐานต่อโพสต์	5 468	937	5.84×
การเข้าถึง (ยอดดู ÷ ผู้ติดตาม)	18.00%	3.44%	5.23×
อัตราการมีส่วนร่วม	0.93%	1.55%	0.60×

บัญชีอื่นในช่วงนี้ → เปรียบเทียบกับบัญชีอื่น → ค่าอ้างอิงเหล่านี้คำนวณอย่างไร →

Growth & engagement

How the posts we collected actually performed: views and reaction rate post by post, what the audience did with them, and where the follower count goes.

Views per post

5.3K10 Aug

9.6K

4.4K

5.5K20 Aug

61.1K23 Aug

3.1K

8.8K

19.8K29 Aug

Last 9 collected posts, oldest on the left. The scale is logarithmic: one post can outrun the rest a hundred times over.

Engagement rate per post

1.73%10 Aug

0.56%

0.96%

1.12%20 Aug

0.93%23 Aug

0.64%

0.66%

1.30%

0.81%29 Aug

Reactions — likes, reposts, replies and quotes — divided by views. Median for 10K–100K accounts is 1.55%.

What the audience does

Likes56.6%959 in total

Reposts4.9%83 in total

Replies2.5%43 in total

Quotes0.4%7 in total

Bookmarks35.5%601 in total

Share of every reaction we collected for this account. Replies mean argument, reposts mean endorsement, bookmarks mean the post was worth keeping.

The follower curve appears once this account has two daily snapshots — we take one a day, and this one is on its first.

โพสต์ล่าสุด

เทียบกับบัญชีขนาดเดียวกัน

Growth & engagement

Views per post

Engagement rate per post

What the audience does

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