Optional stopping and the false discovery rate

An undergraduate training in statistics tells us that sequential testing with optional stopping inflates the false positive rate, but exactly how much it inflates it is less intuitive. Sometimes, the metaphor of rolling a 20-sided dice every time a statistical test is run (assuming alpha = 0.05). However, whereas each roll of the dice is independent, running a new instance of a test on a slightly data set after adding a number of participants is not fully independent.

How old is old? Teaching regression with open data

Research questions What age would people chose to be if given the choice? How old is “old”? Do opinions about ‘how old is old’ change with one’s own age? Open data This data was collected on Project Implicit and is freely available under a CCO license on the Open Science Framework. Specifically, I took the data from the Age related Implicit Association Test collected in 2015. # dependencies ------------------------------------------------------------ library(tidyverse) library(psych) library(knitr) library(broom) data_trimmed <- read_rds("data/data_trimmed.