Absolutely agreed about Occam's Razor and stats - but I don't think T, T, R is a good example.
Of course TT&R is not the best example of how Occam’s razor can be misleading. But, of course, I chose that particular example to emphasise the parallel between cycle helmets and seat belts. I strongly suspect that most of us (it certainly applied to me) initially approached both issues with the same assumption – that the safety intervention is effective. But in the case of cycle helmets, most of us who look at the data with a reasonably open mind then conclude that our assumption was wrong; the advocacy of cycle helmets, and perhaps even the mere wearing of them, actually increases risk. And we now get irritated with people who, in respect of cycle helmets, insist on maintaining their initial assumption and won’t address the data. Whereas they, no doubt, can’t understand why we are pushing convoluted and counter-intuitive (they might even say “preposterous”) interpretations of some of the studies, and why we keep bleating on about risk compensation.
The parallel with seat belts is not perfect. For starters, there’s no dispute that if you have an accident, a seat belt will help, whereas there certainly is dispute as to whether, if you have an accident, a cycle helmet will help. But there are parallels. Knowing what we know about risk compensation as it applies in cycling – knowing what we know about how the biggest effect of helmet wearing is in knock-on effects on people’s behaviour rather than the immediate effect of the helmet – would we not be surprised if those effects didn’t operate in motoring as well? I don’t know to what extent these various things apply (Adams claims 100% risk compensation, and I doubt that is true, but I also doubt 0% is true either), but I sure as heck want to interrogate any relevant data to try to find out. And there's a parallel about our willingness to let our assumptions be challenged by the data.
I'm frankly not that interested in the impact of single interventions.
I agree that in general it’s not meaningful to try to separate the effect of individual overlapping and progressive safety interventions. The reason why seat belts are an exception is because of that step change in usage in 1983. To all of us interested in modelling and data, a step change of a factor of 2 in one of the explanatory variables is a godsend – we’d better see some impact on the output, or be prepared to ask ourselves some searching questions about our model.
Does making a driver feel safer cause them to drive less safely, and does a driver driving less safely lead to bigger risks for cyclists and pedestrians? I’d be absolutely amazed if this wasn’t true to some extent. Here is the results from a broadly pro-seat belt analysis:
They were arguing that the increase in cyclist and pedestrian (and back-seat passenger) injuries did not outweigh the reduction in front-seat injuries, so seat belts are a Good Thing. Maybe they’re right or maybe they’re not about whether the overall balance is positive (there’s debate as to how much of the reduction was attributable to changes in drink-driving law in the same year). But it looks to me like further reinforcement that risk compensation eats up at least some of the benefits of road safety measures .... and as often as not, it’s we cyclists who bear the consequences.