How to Perform Column Comparisons With Missing Data

Pairwise inclusion of missing values is the default option for comparing columns in a grid question. This article shows you the different options for column comparisons.

Requirements

• One or more tables structured as follows:
  • A SUMMARY table using one of the following types of variables sets: Numeric - Grid, Binary - Grid, Nominal - Multi where the variables are in the columns of the tables.
  • A crosstab where the variable set in the Columns is a Binary-Multi.

Method - Pairwise inclusion of missing values

This is the default option. What it means is that when columns are compared, they are compared using only respondents with complete data on all the variables that correspond to the columns. Casewise deletion is employed if an ANOVA-Based Column Comparison has been specified.

Method - Casewise exclusion of missing values

This involves only performing comparisons using respondents with complete data on all the columns being compared. This occurs automatically when using ANOVA-Based Column Comparison. It can be made to occur with any table by application of a filter.

Method - Dependent tests

These tests use all the data that is available for performing the test. To apply dependent tests:

1. Select the table or tables in which you wish to modify the statistical testing assumptions.
2. Select Appearance > Significance > Advanced.
3. On the Test Type tab, change the Proportions test > Survey Reporter Proportions or, if testing means, Survey Reporter Means.
4. On the Column Comparisons tab, change Overlaps > Dependent. 
5. Click Apply to Selection or Set as Default.

Next

How to Apply Significance Testing in Displayr

How to Investigate Your Statistical Significance Testing