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16.2 Performing Analysis

To perform regression analysis, open a spreadsheet and click the Analysis-> Perform Regression menu item. This feature is currently supported for spreadsheets with only one column set as dependent. Categorical dependent columns are currently not supported.

Activating the Perform Regression menu item will open a regression window where various regression options can be changed. A list and brief description of these options is as follows:

Figure 16.2:

Selecting Perform Regression from a spreadsheet menu

16.2.1 Covariates

Linear regression (on the dependent variable) may be done using one or more binary, continuous, or categorical variables (“covariates”) and/or ﬁrst-order interactions between these variables.

To include a covariate in the analysis, ﬁrst click the Add Covariate button. This will open a dialog allowing you to select the covariate(s) that you would like to use during analysis. Then, select the covariate(s) that you would like to include, and click Add. If you would like to add all columns as covariates, click Add All. The selected covariates will be shown in the “included covariates” list. To remove a covariate, select the covariate(s) that you would like to remove, and click Remove Covariate. This will remove the item from the “included covariates” list, and thereby be excluded from the analysis. To remove all covariates click Clear Covariates.

Figure 16.3:

Selecting covariates

To include ﬁrst order interactions, click the Add Interaction button located in the lower right corner of the group. This will open a dialog which displays two lists, each containing all of the column names within the data. Select the term(s) from each of the two lists which you would like to include, and click Add. All selected items from the list on the left will be paired with all selected items from the list on the right, and an item for each pair will be added to the list in the lower right of the regression window. If any of the selected items in either window represent categorical columns, then sub-items representing the dummy variables used in regression for each category will be paired with the items or sub-items from the other window. (Values from each pair are multiplied to create a “new” covariate, which is then used in the regression.)

When you have added all of the interactions that you are interested in, click Close to return to the regression window. All listed interactions will be included in the analysis, so unwanted interactions must be removed in order to exclude them. To remove an interaction, select the item(s) that you want to remove and click Remove Interaction. To remove all interactions, click Clear Interactions.

Figure 16.4:

Selecting ﬁrst-order interactions

Figure 16.5:

Regression window with included covariates and interactions

16.2.2 Type of Regression

You may choose to perform:

Linear or Logistic Regression: checking this option speciﬁes that a single linear or logistic regression will take place. In the case of a binary dependent data column, the regression will be logistic, for an integer or real dependent data column, the regression will be linear.
Stepwise Regression: checking this option speciﬁes that the linear or logistic regresssion should be done as a stepwise regression procedure (17.5.2 or 17.12.2). If you are running stepwise regression, you will also be able to specify a P-value cutoff.

16.2.3 Permutation Tests

You will also have the option of whether or not to perform permutation tests. if you select permutation testing, the dependent variable is randomly permuted a designated number of times, and the selected regression is performed for each permutation. The regression results will show the permuted P-value as the percentile of the permutations in which the P-value is less than or equal to the observed P-value.

16.2.4 Create Residual Spreadsheet With Covariates

If this option is checked, a residual spreadsheet will be created along with the results view from the regression. This spreadsheet will contain the actual, predicted, and residual values for each sample, as well as the spreadsheet values for the covariates and interaction terms.

Figure 16.6:

Example residual spreadsheet

16.2.5 Output and Running the Regression

Click Regression to start the regression procedure (the regression window will remain open, allowing for further regressions until the “close” button is clicked). Note that sometimes the regression may fail. (See 17.7 and 17.13.)

For an explanation of the statistical results shown in the viewer, please see 17.7.2 (for linear regressions) or 17.13.2 (for logistic regressions).

Figure 16.7:

Example regression results window

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