Driver (Importance) Analysis contains a more technical discussion of this and alternative ways of computing importance. Dependent and independent variables may be any non-text variables from the same data file in the project. All input variables are treated as numeric under the linear regression model.
Sign
For Q 4.9.1 or later, (positive and negative) signs are applied to driver analysis scores to match the signs of the corresponding linear regression coefficients from the model including all of the independent variables. Thus the direction of the influence of each independent variable is presented in the scores, in addition to the magnitude. The magnitudes of the driver analysis scores (except for Elasticity) are normalized to sum to 100%. Statistical tests are conducted on the signed raw scores, and the value of test statistics may be different from previous versions, resulting in different test results.
R-squared
The R-Squared statistic is presented at the bottom of the output table. It is computed using a (weighted) linear regression with all of the independent variables.
Crosstabs
A crosstab with a Pick One, Pick Any or Date question may be created by selecting such a question in the brown drop-down. A separate driver analysis is conducted for each category in the question in the brown drop-down, which corresponds to a column in the crosstab. The significance in each crosstab cell is determined according to Testing the Complement of a Cell, i.e. a t-test is conducted comparing whether the raw score in the cell is statistically different from the raw score obtained from the complement of the category.
Charts
Certain types of charts (e.g. bar and column charts) may be created from the driver analysis table. As with tables, only certain statistics are valid for charts.
Inaccurate tooltips
The score and confidence bound are written over the top of existing statistics. However, the tooltips will relate to the original statistics, and so should be ignored.
Further reading: Key Driver Analysis Software
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