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.