Question

If you were to investigate the association between outcome Y being categorical and exposure X, and you treat X as a factor with 4 levels. Which model fits best?A) Yi = a + ß2x2 + ß3x3 + ß4x4B) log odds = a + ß2x2 + ß3x3 + ß4x4C) exp(y) = a + ß1x1 + ß2x2 + ß3x3 + ß4x4D) log odds = a + ß1x1 + ß2x2 + ß3x3 + ß4x4E) Yi= a + ß1x1 + ß2x2 + ß3x3 + ß4x4

Answer 1

Yi= a + ß1x1 + ß2x2 + ß3x3 + ß4x4

Answer 2

Answer:

Data that can be categorised or grouped using names or labels is known as categorical data. Yi = a + ß2x2 + ß3x3 + ß4x4B.

Explanation:

What do you meant by categorical data ?

Using diverging stacked bar charts, contingency tables, and Pearson's Chi-squared tests, we recently provided some fundamental methods for summarising and analysing categorical survey data. Although these techniques are a fantastic place to start when exploring categorical data, generalised linear models can be used to conduct a more thorough investigation.

In order to investigate potential links with other explanatory variables while analysing a continuous response variable, we typically employ a simple linear regression model. For instance, we might look into the correlation between a response variable, like a person's weight, and other explanatory factors, like their height and gender.

Therefore the correct answer is option A) Yi = a + ß2x2 + ß3x3 + ß4x4B)

To learn more about categorical data refer to :

https://brainly.in/question/46012448

https://brainly.in/question/47149681

#SPJ3