Gianco Angelozzi-Blanco, MSc.

All animals are awesome, but some are just more awesome-er than others. Here are five reasons why shorebirds are the most awesome animals in the world! wingthreads.com/5-reasons-why-…

Ustedes pidieron memes venezolanos: Bjork's Caracas Boys -->>>

🇻🇪 LAS TIDAWINAS: Como el día de hoy es el día de la visibilidad trans 🏳️‍⚧️, es buen momento para hablar de esta poco conocida comunidad de mujeres transgénero de la etnia Warao del Delta del Orinoco, aquí en Venezuela.

New paper! Climate change is modifying the distribution of many species. In Patagonia, changes in temperature and precipitation over the past 60 years are already having significant impacts on ecosystems and the species that inhabit them. In this study, doi.org/10.1016/j.bioc…

TEAM VENEZUELA 🇻🇪 CHAMPS 🏆 #WORLDBASEBALLCLASSIC

New paper with @mugartelewis1 and @_carlallq10 on Andean shorebirds phenology is out in Ecosphere, where we combined citizen-science and field data to decipher nest timing of understudied species esajournals.onlinelibrary.wiley.com/doi/full/10.10… #mountains #bird #shorebird

Understanding probability is essential in data science. In 4 minutes, I'll demolish your confusion. Let's go!

Venezuelan Catholics during Lent

Quedé mínimo común múltiplo, verbo to be, escuchamos y no juzgamos, escuchamos y juzgamos, escuchamos y nos agarramos a coñazos, taki taki rumba, estaba paralizado con mucho miedo y no me podía mover, quedé ice, frío, hielo, quedé aguda, grave y esdrújula quedé vemos y juzgamos, quedé plano cartesiano, quedé arepa tiesa.

Me pasé el feriado haciendo esto

Equity in science is a beautiful lie — and I’m done pretending nature.com/articles/d4158…

Libgen, Sci-Hub, and Z-library had millions of pirated academic books and papers. So, they were shut down. We shouldn't use them anyway. We should help billion-dollar academic publishers get richer. Anyway, here's how to access these libraries: Don't do this!

To honor the life and legacy of Dr. Shiloh Schulte, the Schulte & Bateman Families have created a GoFundMe page to help support Shiloh’s family during this incredibly difficult time, with a special focus on securing a bright future for his daughters. gofundme.com/f/honoring-dr-…

Competition has really ruined it... I had my suspicions, this just adds to the pile of evidence.

**NEW RESEARCH ** Some top-ranked countries inflate species counts on @Team_eBird's #GlobalBigDay 📊 Colombia, Peru and Brazil can show ~1.5-3X higher reports vs normal days—likely from competition. Download the PDF at my @ResearchGate profile!

NEW PAPER: Migrating common snipes in better condition show stronger immune responses, suggesting high-quality individuals maintain immunity. Abundant food at stopovers may help replenish reserves for immunity. ➡️ vist.ly/3mzcari #ornithology #migration #EcoImmunology

my snake buttercup says rise and grind 🫡

feliz 5 de marzo a todo el que lo celebra

I recently made a very popular LinkedIn post about Simpson's Paradox, which resulted in an engaging conversation. Paul Julian made a great comment on the relationship between Mixed Effects Models and Simpson's Paradox that I wanted to share with you. He pointed out that when specified correctly, Mixed Effects Models can avoid being fooled by Simpson's Paradox. Unlike a naive linear model that analyzes all data at once, which might lead to misleading conclusions, mixed effects models separate fixed effects (consistent effects across all groups) and random effects (group-specific deviations from the overall trend). This allows the model to account for variations both within and between groups, leading to more accurate interpretations. In the plot below (generated from reproducible code – thanks, Paul!), you can see how different models compare: 🔹 Fixed Effect (black line): Captures the overall relationship, assuming it is the same across all groups. 🔹 Group Linear Model (dashed red line): Shows the trend within each subgroup, revealing how group-specific relationships can differ. 🔹 Naive Linear Model (gray line): Fails to account for subgroup differences, which can lead to misleading conclusions due to Simpson's Paradox. 🔹 Random Effect (blue line): Captures the variation between groups, allowing for group-specific deviations from the fixed effect. Here's the original post: linkedin.com/posts/joachim-… Important Notes: Mixed effects models offer a flexible framework to address Simpson's Paradox, effectively capturing both group-level and overall trends. However, they have limitations and alternative approaches should be considered. Mixed models, like any statistical tool, can be mis-specified if key variables are omitted. In certain cases, simpler models like OLS can handle group effects just as effectively, provided the predictors are correctly specified. For longitudinal or clustered data, marginal models like GEE or MMRM may be better suited when the goal is to estimate population-average effects, especially since mixed models focus on conditional, subject-specific effects. Additionally, Simpson’s Paradox requires careful causal understanding. Grouping variables can either be confounders or colliders, which influences the choice of model. An inappropriate adjustment can lead to incorrect conclusions, making it crucial to understand the causal structure before deciding whether to use a mixed model or a simpler approach. For regular tips on data science, statistics, Python, and R programming, check out my free email newsletter. Click this link for detailed information: eepurl.com/gH6myT #programmer #datastructure #database #datascienceeducation #DataViz