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1.5 SUMMARY

In this chapter we introduced structural equation modeling by describing ebasic types of

variableslatent, observed, independent, and dependentand basic types of SEM models

regression, path, confirmatory factor, and structural equation models. In addition, we gave a brief

history of structural equation modeling and a discussion of the importance of SEM. The chapter

concluded with information about where to obtain the structural equation modeling software

programs used in the book. In chapter 2 we consider the importance of examining data for issues

related to measurement level (nominal, ordinal, interval, or ratio), restriction of range (fewer than

15 categories), missing data, outliers (extreme values), linearity or nonlinearity, and normality or

nonnormality, which affect all statistical methods, and especially SEM applications.

EXERCISES

1. Define the following terms:

a. Latent variable

Latent variable: an unobserved variable that is not directly measured, but is computed usingmultiple observed variables.

b. Observed variable

Observed variable: a raw score obtained from a test or measurement instrument on a trait ofinterest.

c. Dependent variable

Dependent variable: a variable that is measured and related to outcomes, performance orcriterion.

d. Independent variable

Independent variable: a variable that defines mutually exclusive categories (e.g., gender, region,

or grade level) or, as a continuous variable, influences a dependent variable.

2. Explain the difference

2. Explain the difference between a dependent latent variable and a dependent observed variable.

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A dependent latent variable is not directly measured, but is computed using multiple dependent

observed variables. A dependent observed variable is a raw score obtained from a measurementinstrument or assigned to a criterion variable.

3. Explain the difference between an independent latent variable and an independent observed

variable.

An independent latent variable is not directly measured, but is computed using multiple

independent observed variables. An independent observed variable is a raw score obtained froma measurement instrument or assigned to an attribute variable.

4. List the reasons why a researcher would conduct structural equation modeling.

a. Researchers are becoming more aware of the need to use multiple observed variables tobetter understand their area of scientific inquiry.

b. More recognition is given to the validity and reliability of observed scores frommeasurement instruments.c. Structural equation modeling has improved recently, especially the ability to analyzemore advanced statistical models.

d. SEM software programs have become increasingly user-friendly5. Download the student versions of Amos, EQS, and LISREL from the websites given in thischapter.

a. Amos: http://www.smallwaters.com/

b. EQS: http://www.mvsoft.com/c. LISREL: http://www.ssicentral.com/