Ribbon bar. Select the Statistics tab. In the Base group, click Multiple Regression to display the Multiple Regression Startup Panel.

Classic menus. On the Statistics menu, select Multiple Regression to display the Multiple Regression Startup Panel.

The Startup Panel contains two tabs: Quick and Advanced.

See also the Multiple Linear Regression Index, Overviews, and Examples.

OK. Click the OK button, after you have specified Variables, to display the Multiple Regression Results dialog box, the Review Descriptive Statistics dialog box, or the Model Definition dialog box.

Cancel. Click the Cancel button to close the Startup Panel without performing an analysis.

Options. See Options Menu for descriptions of the commands on this menu.

Open Data. Click the Open Data button to display the Select Data Source dialog box, which is used to choose the spreadsheet on which to perform the analysis. The Select Data Source dialog box contains a list of the spreadsheets that are currently active.

Select Cases. Click the Select Cases button to display the Analysis/Graph Case Selection Conditions dialog box, which is used to create conditions for which cases will be included (or excluded) in the current analysis. More information is available in the case selection conditions overview, syntax summary, and dialog box description.

W. Click the W (Weight) button to display the Analysis/Graph Case Weights dialog box, which is used to adjust the contribution of individual cases to the outcome of the current analysis by "weighting" those cases in proportion to the values of a selected variable.

Weighted moments. Select the Weighted moments check box in order to specify that each observation contributes the weighting variable's value for that observation. The weight values need not be integers as the procedures available with Multiple Regression can use fractional case weights in most computations. Some other procedures use case weights as integer case multipliers or frequency values.

DF = W-1 and N-1 options. Use
the options in the DF = group
box allows to base some statistics related to the moments (e.g., standard
deviations and variances, skewness, kurtosis) on the sum of the weight
values for the weighting variable if the W-1
option button is set or on the number of (unweighted) observations if
the N-1 option button is set.
The sums (and means), and sums of squares and cross products will always
be based on the weighted values of the respective observations. However,
in computations requiring the degrees of freedom (e.g., ANOVA table, statistical
significance of parameter estimates), the value for the degrees of freedom
can either be computed as the sum of the weight values minus one (W-1), or as the number of observations
minus one(N-1).

Note: weighted least squares. In some cases it is desirable to apply differential weights to the observations in a regression analysis, and to compute so-called weighted least squares regression estimates. This method is commonly applied when the variances of the residuals are not constant over the range of the independent variable values. In that case, one can apply the inverse values of the variances for the residuals as weights and compute weighted least squares estimates. (In practice, these variances are usually not known, however, they are often proportional to the values of the independent variable(s), and this proportionality can be exploited to compute appropriate case weights.) Neter, Wasserman, and Kutner (1985) describe an example of such an analysis, which is also discussed in the Examples section of Nonlinear Estimation. To compute weighted least squares estimates, choose the desired weight variable, and then select the Weighted moments and N-1 options on the Multiple Regression (Startup Panel).

MD deletion. Missing data can be deleted Casewise, Pairwise, or by Means Substitution depending on the option selection under MD deletion. These options are active only if Raw Data is specified as the Input file (see Multiple Regression Startup Panel - Advanced tab).

Casewise. Select the Casewise option button to include only the cases that do not contain any missing data for any of the selected variables in the analysis.

Pairwise. Select the Pairwise option button to exclude cases from the calculation of correlations involving variables for which they have missing data. In subsequent analyses, all tests of statistical significance in that instance will be based on the smallest number of valid cases found in any of the selected variables.

Mean substitution. Select the Mean substitution option button to replace missing data by the means for the respective variables (for this analysis only, not in the data file).