You can’t make an educated guess that a combination of multiple factors is no greater than the sum of their individual effects, and indeed, when you’re talking about disease states, this is the OPPOSITE of what you should assume. The harm done to your body taxes its ability to deal with harm; the more harm you apply to it, whatever the source, the worse things get. Your body only has so much ability to fight off bad things happening to it, so if you add two bad things on top of each other, you’re actually likely to see harm which is worse than the sum of their effects because part of each of the effects is naturally masked by your body’s own repair mechanisms.
On the other hand, you could have something where the negative effects of each of the things counteracts each other.
Moreover (and worse), you’re assuming you have any independent data to begin with. Given that there is a correlation between smoking and red meat consumption, your smoking numbers are already suspect, because we’ve established that the two are not independent variables.
In any event, guessing is not science, it is nonsense. I could guess that the impact of the factors was greater than the sum of the parts, and get a different result, and as you can see, it is perfectly reasonable to make that guess as well. That’s why it is called a guess.
When we’re doing analysis, guessing is bad. You guess BEFORE you do the analysis, not afterwards. All you’re doing when you “guess” how large the impact is, is manipulating the data.
That’s why control groups are so important.
Regarding glucocorticosteroid use in pregnancy, there actually is quite a bit of debate over whether or not their use is actually a good thing due to the fact that cortiocosteroids are tetratogens.
And yes, actually, it is generally better not to believe in true correlations than it is to believe in false ones. Look at all the people who are raising malnourished children on vegan and vegetarian diets.
Well, there’s certainly no shortage of evidence that it’s unhealthy for children to be malnourished, so that amounts to defying one true correlation in favor of the possibility of another.
Supposing that there were a causative relation between red meat consumption and mortality, with a low effect size, under what circumstances would you be persuaded to believe in it?
You can’t make an educated guess that a combination of multiple factors is no greater than the sum of their individual effects, and indeed, when you’re talking about disease states, this is the OPPOSITE of what you should assume. The harm done to your body taxes its ability to deal with harm; the more harm you apply to it, whatever the source, the worse things get. Your body only has so much ability to fight off bad things happening to it, so if you add two bad things on top of each other, you’re actually likely to see harm which is worse than the sum of their effects because part of each of the effects is naturally masked by your body’s own repair mechanisms.
On the other hand, you could have something where the negative effects of each of the things counteracts each other.
Moreover (and worse), you’re assuming you have any independent data to begin with. Given that there is a correlation between smoking and red meat consumption, your smoking numbers are already suspect, because we’ve established that the two are not independent variables.
In any event, guessing is not science, it is nonsense. I could guess that the impact of the factors was greater than the sum of the parts, and get a different result, and as you can see, it is perfectly reasonable to make that guess as well. That’s why it is called a guess.
When we’re doing analysis, guessing is bad. You guess BEFORE you do the analysis, not afterwards. All you’re doing when you “guess” how large the impact is, is manipulating the data.
That’s why control groups are so important.
Regarding glucocorticosteroid use in pregnancy, there actually is quite a bit of debate over whether or not their use is actually a good thing due to the fact that cortiocosteroids are tetratogens.
And yes, actually, it is generally better not to believe in true correlations than it is to believe in false ones. Look at all the people who are raising malnourished children on vegan and vegetarian diets.
Well, there’s certainly no shortage of evidence that it’s unhealthy for children to be malnourished, so that amounts to defying one true correlation in favor of the possibility of another.
Supposing that there were a causative relation between red meat consumption and mortality, with a low effect size, under what circumstances would you be persuaded to believe in it?