Abuse of Statistics: Part 1
Well, now is as good as a time as any to start my little blog. We’ll start off with my favourite topic: misuse of statistics. In my personal research, I have found that 90% of researchers abuse statistics (That’s a joke. Laugh).
Now, on to the stupid!
Prenatal and Postnatal Exposure to Cell Phone Use and Behavioral Problems in Children. [via The Indepdent]
Mothers of 13,159 children completed the follow-up questionnaire reporting their use of cell phones during pregnancy as well as current cell phone use by the child. Greater odds ratios for behavioral problems were observed for children who had possible prenatal or postnatal exposure to cell phone use.
…
Exposure to cell phones prenatally-and, to a lesser degree, postnatally-was associated with behavioral difficulties such as emotional and hyperactivity problems around the age of school entry. These associations may be noncausal and may be due to unmeasured confounding. If real, they would be of public health concern given the widespread use of this technology.
Repeat after me: correlation does not imply causation. The researchers of this particular study ran a survey and found a pretty high positive correlation between parents using their cell phones during pregnancy and their kids developing behavioural problems later in life. Until you do a detailed study of the specific interaction between cell phones and pregnancy, a correlation is not sufficient to draw any conclusions about causation. This research found a potential relationship between cell phone use during pregnancy and behavioural problems in kids: that’s great! Unfortunately, their conclusions heavily imply that cell phone radiation causes these behavioural problems, which is a spurious conclusion to say the least.
Now, I am glad that they, at least, did acknowledge that the relationship may be non-causal. However, they should have said that the relationship “may be causal” and assumed a non-causal relationship instead of the other way around. There’s simply not enough information in this study to draw any conclusions about a causal relationship.
They did do some work to remove confounding variables, such as drinking or smoking while pregnant, which is good. However, they failed to realise the multitude of possibilities that could explain this relationship. For example (and I’m not saying these are any truer than their conclusion, but these are alternate possibilities), perhaps that heavy use of cell phones while pregnant is strongly correlated with an inattentive parenting style and inattentive parenting causes behaviour problems. Perhaps the behavioural problems are genetic (so both the mother and child may suffer from these issues) and these behavioural issues cause a tendency to use cell phones a lot more; maybe gossiping or neophilia (love of new things) are symptomatic of these behaviour problems. Perhaps something is causing behaviour problems to crop up in children more often now than in the past and the correlation between cell phone use and these behaviour problems is simply a coincidence, because they both are new. Or, perhaps, as the researchers seem to be fond of believing, cell phone radiation alters the brains of children and causes these behavioural problems. I could go on, but I’ll spare you.
What do all of these these hypotheses have in common? They’re all equally valid and all equally unsubstantiated. The correlation that these researchers found demonstrates one thing and one thing only: there is a correlation. What conclusions you can draw from that correlation requires additional study into the menagerie of possibilities that might explain this correlation.