A really poor study with exceedingly bad use of statistics, but don't believe me, read this rebuttal from William M. Briggs (statistician to the Stars)
http://wmbriggs.com/blog/?p=5118
"When the kids became 33 and 30 year olds, they were asked whether they agreed with 13 or 16 questions like, Schools should teach children to obey authority, Family life suffers if mum is working full-time.
Another was, People who break the law should be rehabilitated. Just kidding! Its actually, People who break the law should be given stiffer sentences. The bias in the question wording is ignored.
Another question was, None of the political parties would do anything to benefit me. Is agreeing or disagreeing with that a conservative position? What would the Occupy people say? Another, Being single provides more time to experience life and find out about yourself. Conservative or liberal?
According to the NCDS (pdf), there were about 50 questions, of which only 13 were used. A conservative, then, is whatever Hodson and Busseri say it is. The same thing goes for what a racist is."
"Lo, they found small p-values. The authors appear unaware that samples of this size are practically guaranteed to spit out small p-values.
What makes the study ludicrous, even ignoring the biases, manipulations, and qualifications just outlined, by the authors own admission the direct effect size for g on racism is only -0.01 for men and 0.02 for women. Utterly trivial; close enough to no effect to be no effect, and statistically significant only because of the massive sample size.
The effect size for conservative ideology directly predicting racism is higher (0.69 and 0.51). But all that means is that the questions the authors picked for these two attitudes are roughly correlated with one another. In other words, None of the political parties would do anything to benefit me is crudely correlated with I
wouldnt mind working with people from other races and so forth.
Yet the authors have the temerity to conclude, These results from large, nationally representative data sets
provide converging evidence that lower g in childhood predicts greater prejudice in adulthood and, furthermore, that socially conservative ideology mediates much of this effect.
Truly, statistics can prove anything"