It is also possible to use the older MANOVA procedure to obtain a multivariate linear regression analysis. The string in quotes is an optional label for the output. LMATRIX 'Multivariate test of entire model' The calculation and interpretation of the sample product moment correlation coefficient and the linear regression equation are discussed and illustrated. The syntax to get the complete analysis at once, including the omnibus test for all predictors and dependents, would be: A fitted linear regression model can be used to identify the relationship between a single predictor variable x j and the response variable y when all the other predictor variables in the model are 'held fixed'. To answer these questions, we can use SPSS to calculate a regression equation. Suppose you have predictors X1, X2, and X3, and dependents Y1 and Y2. SPSS will then calculate the mean and standard deviation for each variable in the equation and the correlation between the two variables. Of course, there is more nuance to regression, but we will keep it simple. To do that, you would have to use syntax. Enter all known values of X and Y into the form below and click the 'Calculate' button to calculate the linear regression equation. It also produces the scatter plot with the line of best fit.
In some cases people want a multivariate test for the entire regression. You can use this Linear Regression Calculator to find out the equation of the regression line along with the linear correlation coefficient. Checking the box for Parameter estimates in the Options dialog box produces the regression coefficients for each predictor for each dependent.
The output from this will include multivariate tests for each predictor, omnibus univariate tests, R^2, and Adjusted R^2 values for each dependent variable, as well as individual univariate tests for each predictor for each dependent. To print the regression coefficients, you would click on the Options button, check the box for Parameter estimates, click Continue, then OK. Place the dependent variables in the Dependent Variables box and the predictors in the Covariate(s) box. The simplest way in the graphical interface is to click on Analyze->General Linear Model->Multivariate. You will need to have the SPSS Advanced Models module in order to run a linear regression with multiple dependent variables.