Gender and for the odds ratio for gender. Note that z = 1.74 for the coefficient for Logistic admit gender, nolog */Īdmit | Coef. * Note: the above command is equivalent to. This data represents a 2×2 table that looks like this: Terms of coefficients scales in log odds.
In Stata, the logisticĬommand produces results in terms of odds ratios while logit produces results in In this example admit is coded 1 forĪnd gender is coded 1 for male and 0 for female. Here are the Stata logistic regression commands and Thus, for a male, the odds of being admitted are 5.44 times as large as the odds for a female being admitted. Next, we compute the odds ratio for admission, Now we can use the probabilities to compute the odds of admission for both males and females, Is 0.3 and the probability of not being admitted is 0.7. If you are female it is just the opposite, the probability of being admitted Here are the same probabilities for females,
If you are male, the probability of being admitted is 0.7 and the probability The probabilities for admitting a male are, That seven out of 10 males are admitted to an engineering school while three of 10 femalesĪre admitted. This example is adapted from Pedhazur (1997). Next, we will add another variable to the equation so that we can compute an odds ratio. The odds of success and the odds of failure are just reciprocals of one another, i.e.,ġ/4 =. This looks a little strange but it is really saying that the odds of failure are 1 to 4. Odds are defined as the ratio of the probability of success and the probability
Odds are determined from probabilities and range between 0 and infinity. Use odds ratio to interpret logistic regression?, on our General FAQ page. You may also want to check out, FAQ: How do I