J Hogan

Professor of Biostatistics, Brown University //

Biostatistics / data science / HIV+AIDS / many things in between

[J Hogan @HoganDataLab]

Brown Data Science Initiative launch event on Tuesday Sept 19!

Details at https://t.co/HvMDsaXmNx

@Brown_DSI @BrownBiostats

#dsilaunch

[J Hogan @HoganDataLab]

Well deserved!
Congrats Tyler https://t.co/L07AfjJI92

[Harvard Biostatistics @HarvardBiostats]

Tyler Vanderweele wins prestigious COPSS Presidents' Award for his profound contributions to statistics https://t.co/bidEKuuFpS @HarvardEpi

[jhubiostat @jhubiostat]

Congrats to @rdpeng for being named an ASA Fellow at #JSM2017!

[J Hogan @HoganDataLab]

We're so proud of our @BrownBiostats alum Liangyuan Hu, now on the faculty at Mt Sinai School of Medicine @IcahnMountSinai @lyhuStatree https://t.co/AFA6FyDGya

[Liangyuan Hu @lyhuStatree]

My talk at #JSM2017 featured in @AmstatNews press release. #stats #EHR https://t.co/bwFTvheqId

[J Hogan @HoganDataLab]

111 deceased NFL players donated their brains for research.
110 of them had CTE.

Causal? No.
Startling? Yes.

https://t.co/nFmjs9GP4H

[J Hogan @HoganDataLab]

Evaluation of Chronic Traumatic Encephalopathy in Football Players https://t.co/gfVKV4AQiY

[J Hogan @HoganDataLab]

@OSFramework For me at least, defining new significance thresholds doesn't seem like a step in that direction ... more like a lateral movement. (7/7)

[J Hogan @HoganDataLab]

@OSFramework Even though it's hard in practice, I would argue for statisticians to promote and practice context-driven statistical analyses (6/n)

[J Hogan @HoganDataLab]

@OSFramework The authors acknowledge this as potential criticism but don't offer much by way of rebuttal. (5/n)

[J Hogan @HoganDataLab]

@OSFramework Choosing an arbitrary threshold for 'significance' seems unscientific because it ignores context in which H test is being applied (4/n)

[J Hogan @HoganDataLab]

@OSFramework But it seems to come up short on what I see as the most substantial problem with signif. testing: arbitrary thresholds (.05, .005) (3/n)

[J Hogan @HoganDataLab]

@OSFramework Addressing a major problem in scientific research, endorsed by highly accomplished scientists (2/n)

[J Hogan @HoganDataLab]

Here is an interesting & provocative paper on significance (1/n)

Redefine statistical significance https://t.co/H2T1DeR6m6 via @OSFramework

[Liangyuan Hu @lyhuStatree]

So proud of @BrownBiostats professor Zhijin Wu for voicing opposition to the #ridiculous new law! https://t.co/vZ8fKRM8fm

[J Hogan @HoganDataLab]

Unintended Consequences of Machine Learning in Medicine https://t.co/RgDPxIzk4z

[J Hogan @HoganDataLab]

I like this graphic from @MonaChalabi

Not sure causality is even a relevant issue.

Key point of graphic is clear: US = major outlier https://t.co/PDZhyG8cNj

[Mona Chalabi @MonaChalabi]

#NRA2DOJ https://t.co/wGFRukze9T

[J Hogan @HoganDataLab]

Data Science applied to viral load testing in Kenya:
New publication by @Brownbiostat colleague Tao Liu
@Brown_DSI https://t.co/WUiedQPqK0

[Joe Hogan @jwhogan42]

New article by Tao Liu et al: improving VL testing capacity via pooling
@brownbiostats @ampathkenya @healthybrown
https://t.co/9UZmJxA0hE

[J Hogan @HoganDataLab]

Donald Trump's proposed budget would eliminate the Fogarty Center.

Fogarty Center Leads Global Health Research https://t.co/Lctosin7oX

[J Hogan @HoganDataLab]

Fogarty Center Leads Global Health Research https://t.co/04aszSvux4