Basic Analysis and Graphing - SAS

110 Performing Bivariate Analysis Chapter 4
Fit Orthogonal
Table 4.11 Description of the Fit Each Value Report
Number of Observations
Number of Unique Values
Degrees of Freedom
Sum of Squares
Mean Square
Gives the total number of observations.
Gives the number of unique X values.
Gives the pure error degrees of freedom.
Gives the pure error sum of squares.
Gives the pure error mean square.
Related Information
• “Fitting Menus” on page 115
Fit Orthogonal
The Fit Orthogonal command fits lines that adjust for variability in X as well as Y.
Fit Orthogonal Options
The following table describes the available options to specify a variance ratio.
Univariate Variances,
Prin Comp
Equal Variances
Fit X to Y
Specified Variance Ratio
Uses the univariate variance estimates computed from the samples of X and
Y. This turns out to be the standardized first principal component. This
option is not a good choice in a measurement systems application since the
error variances are not likely to be proportional to the population
variances.
Uses 1 as the variance ratio, which assumes that the error variances are the
same. Using equal variances is equivalent to the non-standardized first
principal component line. Suppose that the scatterplot is scaled the same in
the X and Y directions. When you show a normal density ellipse, you see
that this line is the longest axis of the ellipse.
Uses a variance ratio of zero, which indicates that Y effectively has no
variance.
Lets you enter any ratio that you want, giving you the ability to make use
of known information about the measurement error in X and response
error in Y.
Orthogonal Regression Report
The Orthogonal Regression report shows summary statistics about the orthogonal regression model.