We recently had a dilemma for an OSI publication about the design for the graphs. There will be dozens of these graphs showing the mean score on a given variable for nearly 11000 parents from 10 countries. This example is for household wealt...

We recently had a dilemma for an OSI publication about the design for the graphs. There will be dozens of these graphs showing the mean score on a given variable for nearly 11000 parents from 10 countries. This example is for household wealth which has values ranging from 0 to 16. These are the three

Monte Carlo analysis is a great way to explore the impact of input variable uncertainty on the results of engineering equations, and with vector variables and distribution and sampling functions at its core, R is a natural platform for this analysis. During a recent rainy vacation, I built a Shiny app that applies...

I’ve added mortality data to the lifespan package. A result that immediately emerges from these data is that average life expectancy is steadily climbing. The effect is more pronounced for men, rising from around 66.5 in 1994 to 70.0 in 2014. The corresponding values for women are 74.6 and 76.5 respectively. Good news for everyone.

Based on some feedback to a previous post I normalised the birth counts by the (average) number of days in each month. As pointed out by a reader, the results indicate a gradual increase in the number of conceptions during (northern hemisphere) Autumn and Winter, roughly up to the end of December. Normalising the data

In a previous post I showed that the data from www.baseball-reference.com support Malcolm Gladwell’s contention that more professional baseball players are born in August than any other month. Although this might be explained by the 31 July cutoff for admission to baseball leagues, it was suggested that it could also be linked to a larger

by Joseph Rickert Last week, I mentioned a few of the useR tutorials that I had the opportunity to attend. Here are the links to the slides and code for all but two of the tutorials: Regression Modeling Strategies and the rms Package - Frank Harrell Using Git and GitHub with R, RStudio, and R Markdown - Jennifer Bryan...

In today’s lesson we’ll learn about linear mixed effects models (LMEM), which give us the power to account for multiple types of effects in a single model. This is Part 1 of a two part lesson. I’ll be taking for granted some of the set-up steps from Lesson 1, so if you haven’t done that Lesson 6, Part...

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