So for interpreting our odds ratios remember that our odds ratios are not

probabilities they're functions of probabilities but

they're not probabilities.

An odds ratio of one means no difference, okay?

But on the Logit scale of the log odds ratio zero means no difference.

In odds, [NOISE] often if we have an odds ratio below 0.5 or

above two, that's considered,

I would consider it a kind of strong effect.

It depends very context dependent so if your working in the field of

epidemiology or something like that, you often get very small odds ratios.

1.01 might be significant.

You're looking at giant studies and

the reason that these small odds ratios are important is because they're studying

rather noisy things, like nutrition or something like that.

How nutrition impacts health or something like that.

And you wind up with because of all the various factors that incorporate,

influence this study, you end up with very small odds ratios that are still

meaningful, even if significant.

On the other hand,

you might run a very tightly controlled experimental clinical trial, or

something like that, and then the odds ratios that you would want In order to

declare something kind of meaningful, it would have to be much larger.

So again, this is just less than 0.5 or

bigger than two is a little bit of a benchmark.

But remember, like all benchmarks, we only have a certain amount of utility.

Really, how strong an odds ratio is relative to the scientific setting

is incredibly dependent on the context that you're looking at in.

So the relative risk is another entity that's often thought of

in the same vein as the odds ratio, and many people like it.

So the relative risk is just the ratio of the two probabilities.

And many people like it because they tend to instinctively think a little bit better

in terms of probabilities rather than odds.

And relative probability seems like a reasonable thing to do.

The problem with the Relative risk unlike the Odds is,

it puts in some model constraints there quite hard, so we don't see

relative risk regression for binary variable it's a very common thing to do.

There are some software languages I know are has some packages to do it.

It says has some packages to do it.