R-bloggers

One Way Repeated Measures ANOVA analyzes data where the same subjects undergo multiple conditions or time points. This test helps researchers determine whether significant differences exist in the means of the dependent variable across different conditions. What is One-Way Repeated Measures ANOVA? A One-Way Repeated Measures ANOVA extends the traditional ...

Setup library(tidyverse) # As always library(MASS) # Sampling from a multivariate distributions library(plotly) # For 3D plots OK, but what is AI actually about? Over the past two summers, I taught a statistics and research methods course to psychology students. Generally speaking, these students tend to be a little intimidated ...

Two-way repeated measures ANOVA is a powerful statistical test used to analyze datasets where two within-subject factors (independent variables) are measured multiple times for each subject. This test helps determine if there are significant differences between groups over time or across different conditions while accounting for individual variability. In this ...

Python seems to be everywhere these days, and I’m really into learning languages, so it should come as no surprise that I’m learning a lot of Python. This post serves as a review of Pandas Workout as well as a ‘first impression’ review of the Pandas a...

This post is a first look at Nixtla’s TimeGPT generative, pre-trained transformer for time series forecasting using the nixtlar R package. As described in Garza et al. (2021), TimeGPT is a Transformer-based time series model with self-atten...

Survival analysis is used to predict the time until an event of interest occurs. In this post, I show how to use scikit-learn, xgboost, lightgbm, and conformal prediction for probabilistic survival analysis

A recent conversation with a colleague about a large stepped-wedge design (SW-CRT) cluster randomized trial piqued my interest, because the primary outcome is time-to-event. This is not something I’ve seen before. A quick dive into the literature su...

Simpson’s paradox is when a trend that is present in various groups of data seems to disappear or even reverse when those groups are combined. One sees examples of this often in things like medical trials, and the phenomenon is generally due to ...