New R Package Alert: Tidyheatmap This looks cool 👇

This new R package is wild. It's called ggalign. Here's what it can do:

The ggmulti package is an extension for ggplot2 that allows you to combine multiple visualizations into a single plot. It simplifies the process of overlaying different types of graphs, such as scatter plots, line graphs, and histograms, to compare multiple data sets at once. ✔️

The function is ggstats::ggcoef_model(). It turns your Linear Regression into an easy-to-understand coefficient report. I don't know how many times I've done this the hard way.

Robust standard errors improve the reliability of regression analysis by adjusting for variability in errors (heteroscedasticity). Unlike regular standard errors, which assume constant variance, robust standard errors provide more accurate estimates when the spread of residuals

Causal econometrics in R is a game changer. 🚀 Master experiments, DAGs, differences-in-differences, and more. Don’t miss out—level up your skills now: donskerclass.github.io/CausalEconomet…

Rethinking p-Values in Scientific Research This paper addresses the ongoing debate about p-values and offers innovative solutions to improve statistical practice. Let’s explore the key insights! #Statistics #Research #OpenScience #DataScience tandfonline.com/doi/full/10.10…

Misuse of p-values is a prevalent issue in scientific research. P-values are often misunderstood and misapplied, leading to incorrect conclusions. A p-value measures the probability of obtaining results at least as extreme as the observed ones, assuming that the null hypothesis

Video lectures, UC Berkeley Data 8 Foundations of Data Science spring 2022, fall 2022, spring 2023, by Joseph Gonzalez, Swupnil Sahai, John DeNero data8.org/sp23/ data8.org/fa22/ data8.org/sp22/

Simplify the creation of publication-ready plots! The ggpubr package builds on ggplot2, providing easy-to-use functions for creating clean and stylish visualizations, perfect for reports, articles, and presentations. ✔️ Publication-Ready Graphics: Designed to help you generate

Check out this fun #rstats package Nicola Rennie built to take clean datasets and make them more messy. github.com/nrennie/messy

Circular barplot? 🌀 ➡️ There are now plenty of tutorials in the R and Python graph galleries! - Python with Matplotlib : python-graph-gallery.com/circular-barpl… - R with ggplot2: r-graph-gallery.com/circular-barpl…

Our revolution is back,this Time round ni kufinish kumalo and leave Must Go going to hideout in Cayman islands. #OccupyParliament

iModMix: Integrative Module Analysis for Multi-omics Data biorxiv.org/content/10.110…

New nature A mechanism for why durable weight loss is so difficult: epigenetic memory of fat cells nature.com/articles/s4158… Ferdinand von Meyenn Laura Hinte

"Why do children with #HIV & severe #malnutrition recover slower? Our study using #proteomics reveals how HIV alters bone mineralization, growth factors & immunity, hindering #growth. @Njunge__james James A Berkley CHAIN Network KEMRI-Wellcome

Our JSS article is out! And now I get to focus on {marginaleffects} 1.0.0. Stay tuned. jstatsoft.org/article/view/v…

📚Our #ResearchHighlight: Evans Mudibo et al. have a newly published article titled "Systemic biological mechanisms underpin poor post-discharge growth among severely wasted children with HIV" See the summary and read more! nature.com/articles/s4146…

When applying PCA, understanding each principal component's contribution and how it reveals the data structure is essential. Visualizing more than two components can be challenging, but 3D PCA plots offer a useful solution. A 3D plot visualizes high-dimensional data reduced to

☕ Take a break, grab a coffee, and dive into the latest research! Stroll through the abstract e-posters in the Exhibition Area and make the most of your #NG2025 experience. While you’re there, don’t forget to snap a photo at our booth! 📸