Tips to Using AMOS More Efficiently

Tip 1: Change the AMOS graphics page from portrait to landscape. In the AMOS graphic win- dow, the program will default with the page in a portrait format. Most models take more space from left to right than from top to bottom. If you change the format of the page to landscape, you have

Quick Reference to AMOS Functions

Shortcut Keys for AMOS Functions: F1 = Search Content Directory F2 = “Select one object at a time” button F3 = “Draw Observed Variable” button F4 = “Draw Unobserved Variable” button F5 = “Draw Path (single head)” button F6 = “Draw Covariance” button F7 = “Zoom in” button F8 = “Zoom out” button F9

Introduction to Confirmatory Factor Analysis for SEM Model

Confirmatory factor analysis (CFA) is a statistical technique that analyzes how well your indi- cators measure your unobserved constructs and if your unobserved constructs are uniquely different from one another. In a CFA, an unobservable construct is often referred to as a “fac- tor”. So, when I use the term “factor”, it represents an

How Is a CFA Different From an EFA?

An exploratory factor analysis (EFA) is useful in data reduction of a large number of indicators and can be quite helpful in seeing if indicators are measuring more than one construct. EFAs are typically the first step in determining if an indicator is measuring a construct. In an EFA, the researcher is not denoting

Interpretation of Factor Loadings in CFA

The factor loadings in a CFA estimate the direct effects of unobservable constructs on their indica- tors.If an unstandardized factor loading is 2.0 for the direct effect of Customer Delight ® Delight1, then we expect a two-point difference in the indicator Delight1 given a difference of 1 point on the factor of Customer Delight.While

Setting the Metric in SEM Model

In SEM, each unobserved variable must be assigned a metric, which is a measurement range. This is done by constraining one of the factor loadings from the unobservable variable by assigning it a value of 1.0. The remaining loadings are then free to be estimated. The factor loading that is set to 1.0 is

Model Fit and Fit Statistics of SEM Model

One of the advantages of SEM is that you can assess if your model is “fitting” the data or, specifically, the observed covariance matrix.The term “model fit” denotes that your specified model (estimated covariance matrix) is a close representation of the data (observed covari- ance matrix). A bad fit, on the other hand, indicates

Modification Indices in SEM Model

Modification indices are part of the analysis that suggest model alterations to achieve a better fit to the data. Making changes via modification indices should be done very carefully and have justification. Blindly using the modification indices to achieve a better model fit can capitalize on chance and result in model adjustments that make

CFA Example in AMOS

Let’s say I want to test a simple model that has three unobserved variables. The first vari- able is a concept called “Adaptive Behavior”, which explores customer’s perceptions that an employee adapted their behavior to the customer during an experience. This adaptation could be through verbal interaction or through their direct actions. The perceived

Assessing Convergent and Discriminant Validity of Your Measures in SEM Model

After initially establishing that each indicator is loading on its respective construct and the model has an acceptable fit to the data, we now need to assess the convergent and discri- minant validity of your measures. Just to recap, the basic difference between convergent and discriminant validity is that convergent validity tests whether indicators

If I Have a Weak Factor Loading in SEM Model, Should I Drop It?

If you have a factor loading that is near or below the .70 threshold, it does not mean you need to drop the indicator from the analysis. Complex or newly developed constructs will often have numerous indicators in an attempt to capture a comprehensive aspect of a construct. If you have numerous indicators that

How to Calculate Composite Reliability for SEM Model

I have discussed earlier that reliability of indicators can be explored by calculating Cronbach’s alpha, but this test has had its detractors. Yang and Green (2011) has noted that Cronbach’s alpha is known to overestimate and underestimate values and is “not to be construed as a coef- ficient of internal consistency but rather an

What If I Have a Standardized Factor Loading Greater Than 1 in SEM Model?

A standardized factor loading greater than 1 is stating that you are explaining more than 100% of the variance in an indicator. In this instance, you will also see a negative number in your error term, which is often called a “Heywood case”.The causes of a Heywood case are often the result of an

How Do I Report My CFA Results of SEM Model?

One of the challenges in performing research is analyzing the data, but an equally challenging task is how to report my findings when I am writing it up for a journal or publication. I will give you two templates to follow for writing up CFA results in a table format.There are many accept- able

Measurement Model Invariance Across Groups in SEM Model

Up to this point, we have discussed performing a CFA with a single group. With SEM requir- ing a large sample size, it is pretty common to collect data from two different methods such as online and face-to-face surveys. You will also come across instances where you are surveying two different groups but still

Full vs. Partial Metric Invariance in SEM Model

The test described in the previous section is considered a “full” invariance test. When a model gets more complex, it is increasingly difficult to achieve full invariance. Partial invariance is where multiple estimates/factor loadings per construct need to be equiva- lent (but not all). Based on Hair et al. (2009), if two parameters per

How Do I Know Which Parameter to Free in a Partial Invariance Test in SEM Model?

If you have a significant chi-square invariance test, you need to see what indicators/factor loadings are differing across the groups.You can look at the individual factor loadings for each group and see where you have large differences across the groups. It may just be one construct causing the significant invariance test. Sometimes the differences

Common Method Bias in SEM Model

Over the last 10 years, more and more attention has been paid to the idea of common method bias (CMB) in the measurement analysis phase. Common method bias is the inflation (or in rare cases deflation) of the true correlation among observable variables in a study. Research has shown that because respondents are replying

What If My Test for Common Method Bias Is Significant in SEM Model?

You will need to include the common method variable and its relationships to all the indi- cators when you start testing the structural relationships between constructs. By including the common method variable in the testing of the structural relationships, you are con- trolling for the potential bias of the common method. If you want

What if My Common Method Bias Test Is Non-Significant in SEM Model?

You can state in your research that common method bias is not a substantial concern in your research (do not state that it is not present—it could be present but at very low levels). In your research, you could even present the chi-square difference test showing that common method bias was not prevalent. With