October 3, 2013

People who bought this theory also liked…

An improved version of study that Stuff and StatsChat reported on more than a year ago has now appeared in print. The study found that people who have non-standard beliefs about the moon landings or Princess Diana’s death are also likely to have non-standard beliefs about climate change or health effects of tobacco. It improves on the previous research by using a reasonably representative online survey rather than a sample of visitors to climate debate blogs.

Mother Jones magazine in the US summarised some of the results in this graph of correlations



That’s a horrible graph partly because, contrary to what the footnote says, correlations are not in fact restricted to be between 0 and 1, but between -1 and 1: and in fact the three correlations shown were negative in the research and have been turned around for more convenient display.

The title is misleading: only one of the six `conspiracist ideation’ questions was about 9/11, and it wasn’t a yes/no question, and it wasn’t really about it being an inside job (ie, performed by the government), but about the government allowing it to happen. In the same way, the other three variables aren’t simple yes/no questions, but scores based multiple questions, each on a 5-point scale.

A more-technical point is that correlations, while appropriate in the paper as part of their statistical model, aren’t really a good way to describe the strength of association.  It’s easier to understand the square of the correlation, which gives the proportion of variability in one variable explained by the other.  That is, the conspiracy-theory score explains about 25% of the variation in the vaccine score,  just over 1% of the variation in the GM Foods score, and just under 1% of the variation in the climate change score.

(via @zentree)


Thomas Lumley (@tslumley) is Professor of Biostatistics at the University of Auckland. His research interests include semiparametric models, survey sampling, statistical computing, foundations of statistics, and whatever methodological problems his medical collaborators come up with. He also blogs at Biased and Inefficient See all posts by Thomas Lumley »