Can you have two dependent variables in a regression?
Multivariate Multiple Regression is the method of modeling multiple responses, or dependent variables, with a single set of predictor variables. And in fact that’s pretty much what multivariate multiple regression does. It regresses each dependent variable separately on the predictors.
What type of variable is percentage?
Nominal variables are often summarized as proportions or percentages. For example, if you count the number of male and female A. These percentages may look like a measurement variable, but they really represent a nominal variable, sex.
When to use proportion as dependent variable in regression?
If it’s just a single multiple regression, however, you should look into one of the other methods. A second approach is to treat the proportion as a binary response then run a logistic or probit regression. This will only work if the proportion can be thought of and you have the data for the number of successes and the total number of trials.
How to interpret the following regression in Excel?
In my data set the dependant variable is a percentage with a range 0 to 100. It can be interpreted as the probability or proportion as well. Ex:- Number of correct answers provided by the respondents out of 14 questions in a questionnaire.
Do you use percentage variable in logistic regression?
You have a percentage variable in a sense, but that’s just a way to display your data in a simplified manner. In another sense, you have a count of obese children out of a known total of kids. That is, you have binomial data. Thus, you should use logistic regression, using the counts of actual children.
When is it possible to use multiple linear regression?
Is it possible to use multiple linear regression when the dependant variable is a “percentage” with a range from zero to hundred? In my data set the dependant variable is a percentage with a range 0 to 100. It can be interpreted as the probability or proportion as well.