- Thread starter FeniaWy
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So I get what model you are using, but did not follow the formatting of the variables. Total number of infarctions per person? So you are writing about a count variable?

Logistic regression is a generalized linear model which uses the bernoulli distribution as the response family and the logit as the link function.

I happened to use LR (with both continous and categorical predictors) here:

https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0192039

You may want to have a peek just to see how I interpreted the ORs.

the dependent variable is a continuous variable (total number of infarcts per person)

But maybe you mean ratio scale. So the four infarcts are twice as many as two infartcs. But for an interval variable like temperature four degrees of Celsius in not twice as much as two degrees of Celsius.

For the variable number of infarcts it would better to specify a Poisson distribution with a log link (and skip the talk about odds ratios, which just seems to confuse).

Thanks!

I happened to use LR (with both continous and categorical predictors) here:

https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0192039

You may want to have a peek just to see how I interpreted the ORs.

Thanks!

What is your sample size and design of the study? Also provide a distribution of the outcome variable (histogram).

Thanks.