"Data Not Normal? Just Log-Transform it."

You can find it in textbooks, StackOverflow, and hear it from your colleague.

And it's not always wrong, but it's way more dangerous than we tend to realize.

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#StatSky #Biostats #Biotech

Thank you to everyone who applied to the #PCE and to those who referred colleagues. We can’t wait to welcome the PCE Class of 2026 @hsph.harvard.edu in just a few months!

#Boston #ClinicalResearch #Biostats #Epi

You Need an Analysis. Which Statistical Test to Use?

Hey there, why not ask Claude?

With LLMs, the bottleneck is no longer the speed of access to information or the speed of content generation, but the effort needed to verify the outputs.

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#StatSky #EpiSky #BioStats #CausalSky

"Participants with an ED discharge outcome of death were excluded from the final analysis as this impacted on their re-presentation rate."

Hmmmmmmm.....

#statsky #biostats

The 2025 Biostatistics Research Day poster presentation winners pictured with Prof. Tony Panzarella, Prof. Olli Saarela, & members of the Corey family—Mary Corey and her son Brennan—who sponsor the 3 Paul Corey Memorial poster prizes.

#2025DLSPHwrapped #Biostats

KHstats - A Day in the Life of a Biostatistician Thoughts and doodles on (bio)statistics, causal inference, data visualization, R programming, etc.

Random find (searched something else and stumbled on it) today: a blog on life as a biostatistician. Didn't know much about the field before, but now I'm down a rabbit hole reading about it. Anyone here work in #biostats?
www.khstats.com/blog/ditl/

SERVITORI DI TUTTE LE SCIENZE? IL RUOLO DEGLI STATISTICI NEL PROGRESSO SCIENTIFICO - APPLICAZIONI IN BIOMEDICINA | Dipartimento di Scienze Statistiche | Università di Padova UniPD

Just one week before being back @ #Unipd, for what is now a traditional end-of-the-year motivational lecture on the role of statisticians in biomedical sciences

Friday, Dec 12. Dept of Statistics. Drop a message if you'd like to chat

#biostats #rstats #Statsky

www.stat.unipd.it/servitori-di...

Three university students debating loudly in the quiet zone of the train about when to use t-test, one-way ANOVA and two-way ANOVA. Trying to memorize the rules before their exam.
Fond memories for me from undergrad stats course. 🥸 TBH I didn’t understand those concepts till much later!
#biostats

A model citizen for early detection - Cancer Research UK - Cancer News Fresh from her Impact Award, Professor Ruth Etzioni talks mathematical models, overdiagnosis and why modellers must explain their working…

Following her 2025 Early Detection Impact Award, Ruth Etzioni is profiled by @cancerresearchuk for her work modeling cancer screening.

Insightful piece on balancing benefit, harm & trust in early detection.

🔗 news.cancerresearchuk.org/2025/10/23/a...

#EarlyDetection #Biostats #FredHutch

Computational and Theoretical Biology As we navigate the era of big data in biological research, advanced computational techniques, such as mathematical models and machine learning algorithms, are ...

Thrilled 👏 to 👏see 👏 @jsb-ucla.bsky.social and Pan Liu’s “mcRigor” paper featured in the Computational & Theoretical Biology Editors’ Highlights at Nature Communications! Well done, Jessica and Pan! 🎉

🔗 www.nature.com/collections/...

#SingleCell #ComputationalBiology #Biostats #NatureComms

Paid Biostatistics Summer Internship 2026 | Weill Cornell Medicine - Opportunities for Youth The Weill Cornell Medicine Division of Biostatistics is now accepting applications for its Paid Biostatistics Summer Internship Program for Summer 2026. This

🚨 Paid Biostatistics Summer Internship 2026 at Weill Cornell Medicine — apply now: wp.me/p23f03-gTs

| More internships: opportunitiesforyouth.org?s=Internship

#Internship #Biostats #PublicHealth #Paid #OFY

🧮 Need to refresh your skills in systematic reviews and meta-analyses for #PublicHealth?

Gain a basis in the design, analysis & interpretation of quantitative systematic reviews of health research #biostats #stats

Running 24-27 Nov 2025

Apply by 3 Nov 🔽
www.lshtm.ac.uk/study/course...

Glucostats: an efficient Python library for glucose time series feature extraction and visual analysis - BMC Bioinformatics Background The advancement of technology and continuous glucose monitoring (CGM) systems has introduced several computational and technical challenges for clinicians and researchers. The growing volume of CGM data necessitates the development of efficient computational tools capable of handling and processing this information effectively. This paper introduces GlucoStats, an open-source and multi-processing Python library designed for efficient computation and visualization of a comprehensive set of glucose metrics derived from CGM. It simplifies the traditionally time-consuming and error-prone process of manual CGM metrics calculation, making it a valuable tool for both clinical and research applications. Results Its modular design ensures easy integration into predefined workflows, while its user-friendly interface and extensive documentation make it accessible to a broad audience, including clinicians and researchers. GlucoStats offers several key features: (i) window-based time series analysis, enabling time series division into smaller ‘windows’ for detailed temporal analysis, particularly beneficial for CGM data; (ii) advanced visualization tools, providing intuitive, high-quality visualizations that facilitate pattern recognition, trend analysis, and anomaly detection in CGM data; (iii) parallelization, leveraging parallel computing to efficiently handle large CGM datasets by distributing computations across multiple processors; and (iv) scikit-learn compatibility, adhering to the standardized interface of scikit-learn to allow an easy integration into machine learning pipelines for end-to-end analysis. Conclusions GlucoStats demonstrates high efficiency in processing large-scale medical datasets in minimal time. Its modular design enables easy customization and extension, making it adaptable to diverse research and clinical needs. By offering precise CGM data analysis and user-friendly visualization tools, it serves both technical researchers and non-technical users, such as physicians and patients, with practical and research-driven applications.

"GlucoStats demonstrates high efficiency in processing large-scale medical datasets in minimal time. Its modular design enables easy customization and extension, making it adaptable to diverse research and clinical needs"

bmcbioinformatics.biomedcentral.com/articles/10....

#datascience #biostats

Happy Postdoc Appreciation Week!🎉

Meet Dongliang Zhang, Ph.D., Postdoctoral Research Associate in Biostatistics.

Zhang has been working on on modeling Positron Emission Tomography imaging data to understand brain changes related to Alzheimer’s disease.
#NPAW2025 #postdocappreciationweek #Biostats

🚨 Bingo, but make it Public Health! 🦠📊
Last week our division hosted an Epi & Biostats-themed Bingo event. Students spotted public health buzzwords in media & movies and we had a blast doing it.
#PublicHealth #Biostats #Epidemiology
@uct-fhs-research.bsky.social

The effect estimate for an outcome could be 27% larger when designated as a primary outcome than a secondary outcome in RCTs, which may be partially attributed to bias. Researchers conducting systematic reviews may need to note whether an outcome was designated as primary or secondary in RCTs, perform sensitivity analyses, and interpret results considering the impact of potential bias.

Among 1073 RCTs from 153 meta-analyses, RCTs designating the meta-analyzed outcome as a primary outcome produced ORs 1.27 (95% CI, 1.14-1.42) higher than RCTs designating the same meta-analyzed outcome as a secondary outcome, possibly due to higher risk of performance, detection bias
#biostats

The ratio of effect size (effect sizes pooled from studies with ITB relative to those pooled from studies without ITB) was 0.71 (95% CI, 0.66-0.78), suggesting that the effect sizes from studies with ITB were exaggerated by an average of 29% in favor of the intervention/exposure.

Given the projected high prevalence and nontrivial influence of ITB, ITB should be considered in studies with survival analyses, and improving reporting standards by researchers as well as collective surveillance from readers, reviewers, and editors is warranted. Future studies should address how ITS may also interact with other trial characteristics and biases in affecting treatment effect estimates.

In a comparison of overall summary results with vs without #ImmortalTimeBias (ITB) in 12 systematic reviews addressing 21 clinical topics, evidence reversal occurred in 5 (23.8%), where results changed from statistically significant to not (or vice versa) after excluding studies with ITB
#biostats

A/Prof @kelamb.bsky.social recently presented at the 46th Annual Conference of the International Society for Clinical Biostatistics (ISCB) in Basel, Switzerland.

Read more: clinicalresearch.mdhs.unimelb.edu.au/news-and-eve...

#Mentoring #PeerSupport #WomeninSTEM #STEM #Biostats #EarlyCareer

🔢 Looking to build your #biostats skills?

Sign up for our online course to gain a basis in design, analysis & interpretation of quantitative systematic reviews & meta-analyses in #PublicHealth

Running from 24-27 Nov 2025

More details 🔽
www.lshtm.ac.uk/study/course...

R workshop on linear regression

Registration for logistic regression using R

📈 Another successful R workshop with 50+ attendees learning about linear regression with R. Don’t miss the next one on logistic regression (swipe to see more details).
🖱️ Check out our website for all upcoming R workshops health.uct.ac.za/school-publi...
#RStats #Biostats #Epidemiology #DataScience

Prepping my Biostats w/ R course after a year off of teaching. Feeling overwhelmed regarding AI/cheating (already bad 1y ago). Interested in what folks have found helpful, especially but not exclusively courses involving math and coding. Please share! #teaching #AI #biostats #R-stats

💊 Using real-world evidence to evaluate drug safety & effectiveness in #pharmacology?

Learn to generate real-world evidence with electronic health record data, tackle biases, apply advanced #stats techniques

Running 20-24 Oct 2025 #biostats

Apply 🔽
www.lshtm.ac.uk/study/course...

📊 Learn to generate real-world evidence using electronic health record data, tackle biases, apply advanced #stats techniques especially in drug safety & effectiveness #biostats #pharmacology

Running 20-24 Oct 2025

Apply 🔽
www.lshtm.ac.uk/study/course...

Planning your JSM day? Don’t miss these ENAR-sponsored talks, posters, and panels happening tomorrow in Nashville!
#ENAR #JSM2025 #Biostats

Planning your JSM day? Don’t miss these ENAR-sponsored talks, posters, and panels happening tomorrow in Nashville!
#ENAR #JSM2025 #Biostats

FREE Introduction to Generalised Linear Models for Ecologists | PR Statistics The FREE Introduction to Generalised Linear Models for Ecologists (FGLM01) is a one-day online course designed to make GLMs approachable for beginners in ecology and data analysis. Participants will e...

Not sure if GLMs are right for your research?

This free intro course is the best way to find out.

Taught live by Dr. Niamh Mimnagh and based on our 10-day GLM course.

Includes worked examples and Q&A.

Aug 12

www.prstats.org/course/free-...

#PhDLife #RStats #GLM #Ecology #Biostats #OpenScience

Introduction to Generalised Linear Mixed Models for Ecologists | PR Statistics Introduction to Generalised Linear Mixed Models for Ecologists (MMIE01) teaches the theory and application of LMMs and GLMMs using R. Participants model hierarchical ecological data with tools like lm...

PhD students: working with repeated measures, nested designs, or hierarchical ecological data?

This course teaches you how to model it properly using GLMMs in R.

Taught live by Dr. Niamh Mimnagh.

Sept 22–26

www.prstats.org/course/intro...

#RStats #GLMM #PhDLife #Biostats #Ecology #OpenScience

Spatial and Spatial-Temporal Modelling Using R-INLA | PR Statistics Spatial and Spatio-Temporal Modelling using R-INLA (SSTM02) provides an in-depth introduction to Bayesian modelling of spatial and spatio-temporal data using the INLA framework. Participants learn to ...

PhD students: if your research involves spatial or temporal data, this course is for you.
Master R-INLA for ecological modelling with expert instruction from Dr. Virgilio Gómez-Rubio.

Sept 22–26
www.prstats.org/course/spati...

#RStats #INLA #PhDLife #SpatialData #Ecology #Biostats #OpenScience

Species Distribution Modelling (SDMs) and Ecological Niche Modelling (ENMs) - PR Statistics Species Distribution Modelling and Ecological Niche Modelling (SDMR06) offers a comprehensive exploration of ENM and SDM techniques using R. Participants learn to model species distributions using algorithms like Maxent, GLMs, and Biomod2. Ideal for researchers in biogeography and spatial ecology, the course blends theory with hands-on coding in R. Topics include model calibration, projection to climate scenarios, and ENM comparison using Ecospat.

PhD students in ecology or biogeography: this SDM course is for you.
Learn how to build, evaluate, and visualise species distribution models using R.
Taught live and online by Dr. Neftalí Sillero.

Sept 22–26
www.prstats.org/course/speci...

#RStats #SDM #PhDLife #Biostats #Ecology #OpenScience

Multivariate Analysis of Ecological Communities Using VEGAN - PR Statistics Multivariate Analysis of Ecological Communities Using VEGAN (VGNR08) is a five-day intensive online course that teaches participants how to analyse ecological community data using the VEGAN package in...

Analyse community ecology data in R using vegan.

This hands-on live course covers ordination, clustering, and multivariate testing with real datasets.
Led by Dr. Antoine Becker Scarpitta.

Sept 15–19
www.prstats.org/course/multi...

#RStats #PhDLife #DataScience #Ecology #Biostats #OpenScience