Multiple Regression

Multiple Linear Regression

Carry out multiple linear regression on up to 45 independent variables, routine provides

Example of Interface :


1. Standard ANOVA and Beta tables
2. Collinearly (Tolerance and VIF)
3. Correlation between independent variables
4. Correlation of betas
5. Co-variance of betas
6. Y, Yhat, confidence limits of Yhat and standardized residuals

Example of regression results :

Data Filter

1. Removal of outliers with user specified cut point


1. Normal probability plots with actual frequencies and expected normal distribution
2. Predicted against actual residuals
3. Actual residuals against X1, X2 .....

Example of regression chart results :

Logistic Regression

Carry out logistic regression on binary dependant variables, routine provides


1. G statistic and beta tables
2. 2 x 2 contingency tables with user adjustable cut values
3. Hosmer and Lemeshow Good of Fit Test Table

Logistic Count Regression

A variation on regular Logistic Regression used when the data is composed of sets of many identical independent observations that can be represented by a single group.

Provides statistics as for regular logistic regression above, as well as expected probabilities for each group.


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