By James L. Arbuckle.
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Extra resources for Amos 17.0 user's guide
About the Data Attig (1983) showed 40 subjects a booklet containing several pages of advertisements. Then each subject was given three memory performance tests. Test recall cued place Explanation The subject was asked to recall as many of the advertisements as possible. The subject’s score on this test was the number of advertisements recalled correctly. The subject was given some cues and asked again to recall as many of the advertisements as possible. The subject’s score was the number of advertisements recalled correctly.
E Use the same method to label the place1 and place2 variances as v_place. It doesn’t matter what label you use. The important thing is to enter the same label for each variance you want to force to be equal. The effect of using the same label is to 44 Example 2 require both of the variances to have the same value without specifying ahead of time what that value is. Benefits of Specifying Equal Parameters Before adding any further constraints on the model parameters, let’s examine why we might want to specify that two parameters, like the variances of recall1 and recall2 or place1 and place2, are equal.
14 Chapter 2 Constraining a Parameter To identify the regression model, you must define the scale of the latent variable Other. You can do this by fixing either the variance of Other or the path coefficient from Other to SAT at some positive value. The following shows you how to fix the path coefficient at unity (1). E In the drawing area, right-click the arrow between Other and SAT and choose Object Properties from the pop-up menu. E Click the Parameters tab. E In the Regression weight text box, type 1.