Top Tweets for #StatThink
New blog article on the unreasonableness of the prior distribution that is effectively used in much of frequentist inference: https://t.co/cVW0lfZQGj @5_utr @PhilosopherMD1 @vandy_biostat #StatThink
New blog article: Controlling how much of a treatment effect on nonfatal outcomes should spill over to mortality, i.e. how to assess mortality effects when you don't have the sample size. https://t.co/6n5RSt3oQe #Statistics #clinicaltrials #StatThink @vandy_biostat
New blog article on superior performance of proportional odds model vs. paired t-test. Graph below shows negligible power loss under an ideal situation for the paired t-test. Thanks for important suggestion from @noah_greifer https://t.co/QE0vMqNzAW #StatThink #Statistics
April issue of Statistical Thinking News has some updates in recommended stats articles plus a few others - https://t.co/QkOrbv6lPg #StatThink @vandy_biostat
Statistical Thinking News has moved to a new site https://t.co/QkOrbv6lPg due to paper(dot)li ceasing operations next month. A new edition is now out. #StatThink #Statistics #statstwitter #rct #clinicalresearch #DataScience @vandy_biostat @VUDataScience @EdgeforScholars
This graph of the decline effect is priceless. Poor publishing standards for "exciting" new findings followed by more rigorous research that finds much less impressive results. @vandy_biostat @VUDataScience @EdgeforScholars #bbrcourse #StatThink
“'How did this get published in PNAS?'” My response: 'well, PNAS is not a good journal.'"
https://t.co/krYbTKXyAw
Regression Modeling Strategies 4-day virtual course May 16-19 taught by myself and @DrewLevy is now open for registration at https://t.co/FGeMeu5YjH #rmscourse @vandy_biostat @VUDataScience @EdgeforScholars #StatThink #Statistics
Log HR progression vs age for breast cancer.
Assuming linearity of age as a predictor is a disaster
Pretending cutpoints exist e.g. age 50 or 70 is a disaster
Good example also of how younger age for breast = bad #radonc #StatThink #rms #bcsm
New blog article in Statistical Thinking: Grant proposal template for developing and validating predictive biostatistical models: https://t.co/MAOs7Y5L8l #StatThink #rmscourse #bbrcourse @vandy_biostat @VUDataScience @EdgeforScholars
#Statistics thought of the day: If you use Bayesian methods for design & analysis of #clinicaltrials it's because you want completely different probabilities than what frequentists compute. Don't ask a Bayesian trial to compute alpha https://t.co/YU9mBafN8D #StatThink
I don't know about my long-term twitter future because of #TwitterTakeover. Please follow me also at @[email protected] #TwitterMigration @vandy_biostat @VUDataScience #StatThink #Statistics #statstwitter #biostatistics #rstats @EdgeforScholars
I finished converting my Statistical Thinking blog at https://t.co/8sdCD3RJoQ from blogdown->hugo->github->netlify to Quarto->manual netlify deployment. MUCH cleaner, with better article formatting and search capabilities. #StatThink @vandy_biostat @VUDataScience @quarto_pub
#Statistics thought of the day:It is not appropriate to compute a mean or run parametric regression on % change unless you first compute log(% change/100 + 1) to undo damage done by % change https://t.co/x0xRn2vf5W #statstwitter @vandy_biostat @VUDataScience #StatThink #bbrcourse
#Statistics thought of the day. #statstwitter @vandy_biostat #clinicaltrials https://t.co/50FXiLCDlN #StatThink
How to Do Bad Biomarker Research - the definitive guide.
New blog article: https://t.co/3nsP2C7oCF #StatThink #Statistics #statstwitter @vandy_biostat @VUDataScience @EdgeforScholars
Wonderful paper. Same issues apply to electronic health record-based research where bias-corrected effective sample sizes can be a small fraction of the apparent sample size: https://t.co/5lX7Fu196Q @vandy_biostat #StatThink @EdgeforScholars @VUDataScience #statstwitter
Pay attention: Big data loses to good data. “A survey of 250,000 respondents can produce an estimate of the population mean that is no more accurate than an estimate from a simple random sample of size 10… data quality matters more than data quantity” https://t.co/TDNMfeRyWh
RT @f2harrell: Contribute to a new topic in datamethods: https://t.co/hNq3Bc3m1O & see if you share my pessimism about big data, precision health, high-dimensional data analysis, and machine learning #Statistics #statstwitter #StatThink #bbrcourse @vandy_biostat @VUDataScience …
Contribute to a new topic in datamethods: https://t.co/rWVFyV9EMe & see if you share my pessimism about big data, precision health, high-dimensional data analysis, and machine learning #Statistics #statstwitter #StatThink #bbrcourse @vandy_biostat @VUDataScience @EdgeforScholars
Cool new article from @LucyStats on statistical thinking and design of analysis: https://t.co/7pXYRoKxWm #StatThink #statistics #statstwitter @vandy_biostat @VUDataScience @EdgeforScholars
#Statistics thought of the day: No matter how well or poorly the proportional odds model fits, its estimated odds ratio is 1.0 if and only if the Wilcoxon statistic is at the null point (concordance probability=U statistic=0.5). https://t.co/KTAnaTrqR3 @vandy_biostat #StatThink
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