Genevieve David

[Sir Michael Marmot @MichaelMarmot]

In what moral universe can this be the right thing to do: the lower the life expectancy of a local area in 2010-12, the greater the cuts to government funding in the subsequent years. Was this a deliberate policy to increase health inequalities?

[Alex Telford @Atelfo]

In 1953, aged 27, Paul Janssen set up a pharma company that would grow into one of the world's largest. Over his career, Janssen and his team brought >70 drugs to market.

Yet, today's drug hunters are likely to retire before discovering even one new medicine. What changed?🧵

[Josep Ferrer @iamjosepferrer]

Struggling with Machine Learning algorithms? 🤖

Then you better stay with me! 🤓

Today I am starting a new series of threads to simplify ML algorithms.
...and Linear Regression is the first one! 👇🏻

[michael parkinson @88xtc]

What do 2,731 incarcerated people have in common?

The Social Determinants of Justice c/o @druthmcc @eileenbaldry in @CrimJustJournal

Authentic health + safety solutions exist outside of criminal justice systems, not in courts + prisons.

See: https://t.co/17rUXpBb5d

[Sir Michael Marmot @MichaelMarmot]

Social determinants of health ... and crime. People can't afford to eat. It means relying on charity or, increasingly, on stolen food. How about remembering: tough on the causes of crime.

[Selçuk Korkmaz @selcukorkmaz]

Multicollinearity in Regression Analysis

1/ Introduction to Multicollinearity
Multicollinearity arises in regression analysis when two or more predictor variables are highly correlated. This means they often change together, making it challenging to isolate their individual effects on the response variable.

2/ Why is Multicollinearity a Problem?
• It can inflate the variance of regression coefficients, leading to less reliable estimates.
• It can result in misleading p-values for predictors, suggesting a variable is insignificant when it is, or vice versa.
• It diminishes the statistical power of the regression model, making coefficients sensitive to small changes in the model.

3/ Detecting Multicollinearity
Look out for:
• High Variance Inflation Factors (VIFs): A VIF > 10 is often considered a sign, but some suggest a lower threshold like 5.
• Pairwise Correlation Matrix: Check for predictor pairs with high correlation coefficients, typically above 0.8.

4/ Common Causes
• Including redundant variables (e.g., using both temperature in Celsius and Fahrenheit).
• Including variables that are mathematical combinations (e.g., total score when you already have average score).
• Survey or questionnaire designs where questions are too similar.

5/ How to Address Multicollinearity?
a. Remove One of the Correlated Variables: Choose based on domain knowledge, or the one that contributes less to the model.
b. Combine Correlated Variables: Create a composite score or use principal component analysis.
c. Regularization Techniques: Ridge or Lasso regression can help by adding a penalty to large coefficients.

6/ Importance of Domain Knowledge
Always consider domain knowledge! Even if variables are correlated, they may have distinct implications in real-world scenarios.

7/ Is Multicollinearity Always Bad?
Not always. If your primary goal is prediction rather than interpretation, multicollinearity might be less of a concern. However, it's always good to be aware of its presence.

8/ Conclusion
Multicollinearity can complicate regression analysis. It's essential to detect and address it for clear and accurate results. Always cross-check with domain knowledge and remember: correlation doesn't imply causation.

#Statistics #DataScience

[Dr Melvin Sanicas @Vaccinologist]

Focus on what you can control. The right way to feel in #control is to #focus on what you can #change within yourself or your #environment, and start taking small steps in the right direction. You cannot control everything. 🖤 💚 💙
#ThoughtForTheDay #WordsOfWisdom #WiseWords

[Vanessa @vanessainstem]

Last year, I saw a tweet about grad school decision advice that truly stuck with me. It said something like: “Would you go with an advisor that would choose students, or science?”

One year into my PhD, I warn everyone to pick the one that would choose students.

[Housing 4 All is Hot @ahouse4all]

I met a 78 year old man who recently started sleeping at a park I take supplies to.

He broke his back working construction. When he got out of the hospital, he had been evicted.

A lifetime of his belongings had been thrown away by his landlord.

Homelessness is that easy.

[Christiane Amanpour @amanpour]

A healthy democracy is at risk over inequality, says former President @BarackObama. "Our democracy is not going to be healthy with the levels of inequality that we've seen, generated from globalization, automation, the decline in unions, obscene inequality."

[Dan @danmurrays]

4 years ago - OpenAI's CEO Sam Altman wrote a blog on How To Be Successful

Here's the breakdown:

[Massimo @Rainmaker1973]

Demonstrator Instructor remotely operating a CAT 982 wheel loader, while simultaneously operating a 352 excavator carving the CAT Symbol into the dirt while he waits for trucks to load

[📹 timothycaterpillar: https://t.co/S4AINvggst]

[Genevieve David @GDavid_MD]

@Teddybird Congratulations, Sec. Ted @Teddybird Herbosa!

[Ilya Shabanov @Artifexx]

This AI search engine answers academic questions truthfully: Consensus

It's like PubMed, Google Scholar and ChatGPT in one.

Ask plain text questions and get papers that factually answer it:
👇

[Mushtaq Bilal, PhD @MushtaqBilalPhD]

Don't use ChatGPT for scientific research. It generates fake citations to papers that don't even exist.

Instead, use System Pro — a AI-powered search engine designed for research.

Ask it a question and it'll give you a summary of relevant (published) papers with citations.

[Jknt @jkntji]

@AndrewYNg @OpenAI Looks good.
I found this openai article for reliable prompts very useful.

https://t.co/RZdjAEE3Zb

[Mushtaq Bilal, PhD @MushtaqBilalPhD]

And if you want to learn how to supercharge your academic writing with the help of AI-powered apps, I have a tutorial for you.

It has more than 170 slides and will help you conceive, develop, draft, and revise your writing project.

You can get it here:
https://t.co/j4tAsr4sua

[Mushtaq Bilal, PhD @MushtaqBilalPhD]

ChatPDF is an AI-powered app that will make reading journal articles easier and faster.

Simply upload a PDF and start asking it questions.

It's like ChatGPT, but for research papers.

Here's how to use it: