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I agree with your argument that only looking at successful examples without taking into account the failed examples might lead to distorted information and wron

I agree with your argument that only looking at successful examples without taking into account the failed examples might lead to distorted information and wrong conclusions. But I critize the simplicity of your model that ignores crucial yet tricky questions like: How long does it take to detect a failure? How can I detect it, which criteria should I use? How to avoid "false positives"? A simple "try and repeat every year"-scheme will most probably lead to 10 failures in 10 years...

mixmax 18y ago
I agree with your criticism - it is a simplified model, and models only give a simpified view of the world. As you point out, ideally there are lots and lots of criteria that should be considered, and that probably have a measurable effect. The big problem is getting the data to do so: You'd have to take some statistically significant amount of projects from the very start (which is where the most interesting part happens in relation to living or dying) and follow them closely until they either die or become successful. It would be an extremely interesting project though.