Can you correlate two dependent variables?
Yes, this is possible and I have heard it termed as joint regression or multivariate regression. In essence you would have 2 (or more) dependent variables, and examine the relationships between independent variables and the dependent variables, plus the relationship between the 2 dependent variables.
What happens when you have two dependent variables?
When multiple dependent variables are different measures of the same construct—especially if they are measured on the same scale—researchers have the option of combining them into a single measure of that construct. Researchers in psychology often include multiple dependent variables in their studies.
Can two variables be combined?
Yes. you can combine the variables and test the relationship. the combination comes in the form of x1 multiplied by x2 etc.
When there are multiple dependent variables in a model?
Multivariate Multiple Regression is the method of modeling multiple responses, or dependent variables, with a single set of predictor variables. For example, we might want to model both math and reading SAT scores as a function of gender, race, parent income, and so forth.
Is it acceptable to have more than one dependent variable explain?
No. The value of a dependent variable depends on an independent variable, so a variable cannot be both independent and dependent at the same time.
Can you have 3 independent variables?
In practice, it is unusual for there to be more than three independent variables with more than two or three levels each. This is for at least two reasons: For one, the number of conditions can quickly become unmanageable.
How many dependent variables are used in multiple regression one one or more two or more two?
It is also widely used for predicting the value of one dependent variable from the values of two or more independent variables. When there are two or more independent variables, it is called multiple regression.
Can you have two independent variables in a study?
Researchers often include multiple independent variables in their experiments. There is one main effect for each independent variable. There is an interaction between two independent variables when the effect of one depends on the level of the other.
What happens if two independent normal random variables are combined?
What happens if two independent normal random variables are combined? Any sum or difference or independent normal random variables is also normally distributed. A binomial setting arises when we perform several independent trials of the same chance process and record the number of times a particular outcome occurs.
When using two predictor variables these variables should be?
When using a multiple regression model, the predictor variables should be independent and unrelated with one another, but related to the outcome variable.
When there are multiple dependent variables, there will be prediction errors for each of the dependent variables. In the example above, there are two dependent variables, Area1 and Area2, so there will be prediction errors for Area1 and also prediction errors for Area2.
What happens when there are multiple dependent variables in a GLM?
In a ordinary GLM, there is a single dependent variable, and the prediction errors have a mean of 0 and a variance that can be computed after the GLM is fitted. When there are multiple dependent variables, there will be prediction errors for each of the dependent variables.
When do multiple dependent variables are different measures of the same construct?
When multiple dependent variables are different measures of the same construct—especially if they are measured on the same scale—researchers have the option of combining them into a single measure of that construct. Recall that Schnall and her colleagues were interested in the harshness of people’s moral judgments.
Which is an example of dependency between correlations?
Overlapping correlations are not the only cause of dependency between correlations. The samples themselves could be correlated. Zou (2007) gives the example of a correlation between two variables for a sample of mothers. The same correlation could be computed for their children.