GLM Basic Examples

  • Example 1: A 2 x 3 Between-Groups Factorial ANOVA Design
    This example is based on a fictitious data set presented in Lindeman (1974). Suppose that we have conducted an experiment to address the nature vs. nurture question; specifically, we tested the performance of different rats in the "T-maze." The T-maze is a simple maze, and the rats' task is to learn to run straight to the food placed in a particular location, without errors. Three strains of rats whose general ability to solve the T-maze can be described as bright, mixed, and dull were used. From each of these strains, we reared four animals in a free (stimulating) environment and four animals in a restricted environment. The dependent measure is the number of errors made by each rat while running the T-maze problem.
  • Example 2: One-Way ANOVA Design
    This example is based on a data set presented in Milliken and Johnson (1992, p. 6). The data came from an experiment that was conducted to determine how six different kinds of work tasks affect a worker's pulse rate. In this experiment, 78 males were randomly assigned to perform 6 different work tasks (13 workers were assigned to be trained on each task). Due to attrition, only 68 workers completed the experiment. On a selected day after training, the pulse rates of workers (number of pulsations in 20 seconds) were measured after the workers performed their assigned tasks for one hour. The data are available in the example data set Pulse.sta.
  • Example 3: Main Effects ANOVA Design
    The data file Adstudy.sta contains 25 variables and 50 cases. These (fictitious) data were collected in an advertising study where male and female respondents evaluated two advertisements. Respondents' gender was coded in variable 1 (Gender: 1=male, 2=female). Each respondent was randomly assigned to view one of the two ads (Advert: 1=Coke, 2=Pepsi). They were then asked to rate the appeal of the respective ads on 23 different scales (Measure01 to Measure23). On each of these scales, the respondents could give answers between 0 and 9.
  • Example 4: Mixed-Model Factorial ANOVA Design
  • Example 5: Mixed-Model Nested ANOVA Design
  • Example 6: Repeated Measures ANOVA Design
  • Example 7: Simple Regression Analysis
  • Example 8: Multiple Regression Analysis
  • Example 9: Response Surface Design
    Box, Hunter, and Hunter (1978, Chapter 15) report a study of the yield of a chemical process. The two factors of interest in that study are the setting of the temperature (variable Degrees) and the amount of Time that the chemical agents are allowed to react. Because we do not expect a simple linear relationship between these factors and the resultant yield, a response surface design is employed. The example data file Composit.sta contains the data from the experiment.
  • Example 10: Mixture Surface Design
  • Example 11: MANCOVA Design