Module 3 – Background

instrument/measurement model, regression, path analysis, and structural equation modeling tools

Required Reading

Review the Module 3 Measurement and Structural Model Concepts PowerPoint slides.

Read the following article and pay attention to how they validated the instrument and substantiated the results.

McAllister, D. J., & Bigley, G. A. (2002). Work Context And The Definition Of Self-How Organizational Care Influences Organization-Based Self-Esteem, Academy of Management Journal, 45(5), 894-904

Optional Reading

Find YouTube Videos on use of SPSS reliability analysis, convergent validity analysis, and regression testing.

Find YouTube Video on use of SmartPLS.

Module 3 – Case

instrument/measurement model, regression, path analysis, and structural equation modeling tools

Assignment Overview

The instructions in the PowerPoint slides will be followed. The student will accomplish measurement instrument/model assessment using SPSS tools then using Smart PLS.

Case Assignment

After reviewing the required readings found in the module background section, accomplish the instructions in the PowerPoint Slide (MODULE 3 CASE INSTRUCTIONS PPT-3).  You will require the use of 4 sets of data files (All 3 start with the name Data for Module 3 – Variables and Indicators – see below – and the 4^th one is called Data for Mediation Analysis.sav) and a macro used in SPSS (59069MB mediation test macro.sps).  When you finish you can upload the files to the Case Assignment.

Data for Module 3- Variables and Indicators – Import to SmartPLS

Data for Module 3- Variables and Indicators – Import SPSS

Data for Module 3- Variables and Indicators – Import to SmartPLS-only 99

Important:

If it has been a long time since you used SPSS or you have never used SmartPLS, look up some You-Tube Videos.

If you do not have a large or dual monitor on your computer, it is highly recommended that you print these PowerPoint instruction slides or you will have challenges executing the assignment.

Assignment Expectations

Students gain practical experience:

1. Assessing measurement instruments and associated measurement models.
2. Assessing relationships between variables in a regression, path, or structural model.
3. Assessing how different statistical analysis software (tools) present different statistics.