# Complex Samples General Linear Model Estimated Means

The Estimated Means dialog box allows you to display the model-estimated marginal means for levels of factors and factor interactions specified in the Model subdialog box. You can also request that the overall population mean be displayed.

**Term.** Estimated means are computed for the selected factors
and factor interactions.

**Contrast.** The contrast determines how hypothesis tests
are set up to compare the estimated means.

- Simple. Compares the mean of each level to the mean of a specified level. This type of contrast is useful when there is a control group.
- Deviation. Compares the mean of each level (except a reference category) to the mean of all of the levels (grand mean). The levels of the factor can be in any order.
- Difference. Compares the mean of each level (except the first) to the mean of previous levels. They are sometimes called reverse Helmert contrasts.
- Helmert. Compares the mean of each level of the factor (except the last) to the mean of subsequent levels.
- Repeated. Compares the mean of each level (except the last) to the mean of the subsequent level.
- Polynomial. Compares the linear effect, quadratic effect, cubic effect, and so on. The first degree of freedom contains the linear effect across all categories; the second degree of freedom, the quadratic effect; and so on. These contrasts are often used to estimate polynomial trends.

**Reference Category.** The simple and deviation contrasts
require a reference category or factor level against which the others
are compared.

To Obtain Estimated Means for Complex Samples General Linear Model

This feature requires the Complex Samples option.

- From the
menus choose:
- Select a plan file. Optionally, select a custom joint probabilities file.
- Click Continue.
- In the Complex Samples General Linear Model dialog box, click Estimated Means.
- Select terms whose levels you want to compare, the contrasts for performing the hypothesis tests, and any necessary reference categories.