I’m modelling some reaction time data, and stumbled upon the shifted log-normal family argument. It’s described as well-suited for modelling reaction time, so I was intrigued.
The residual plot and qqplot of my model show equal variance and generally a normal distribution. However, my summary statistics (Est. error, credible intervals, and R-hat) are way better, when I use a shifted log-normal distribution, than a Gaussian distribution.
I’ve searched the web for general knowledge on the shifted log-normal distribution, its assumptions or when to apply this instead of Gaussian or just log-normal distributions, but without luck.
So my question is:
WHEN do you use the shifted log-normal distribution? What kind of data is it suitable for? And why/when do you choose it over the Gaussian or log-normal distributions?