Get familiar with the SPSS Amos interface
IBM SPSS Amos has an easy interface for applying the Structural Equation Modeling (SEM) test. A number of tests such as maximum likelihood, generalized least squares, unweighted least squares, scale-free least squares, Bayesian estimation, and Browne’s asymptotically distributed free criterion can be easily applied in the SPSS Amos interface.
Launching the SPSS Amos graphics
To launch the working window of SPSS Amos, click on the ‘Amos graphics’ option in the start menu of your computer screen. It looks like the icon below.

This will open the following SPSS Amos graphics window. It is the main window to perform functions like running the SEM test and creating graphs or models.

After importing the dataset draw the variables
Drawing an observed variable
The rectangular shape figure defined by the icon
is used for drawing the observed variables i.e. the ones whose value researcher input. Click on the icon to draw the observed variables. After drawing it, the below image will appear.

Drawing a latent variable
Further, the oval or eclipse-shaped figure is drawn using the
icon for unobserved variables i.e. the latent variable. Click on that icon to draw the observed variables. After drawing it, the below image will appear.

Combining the latent and observed variables
Another option in the Amos is to draw a model which is a combination of latent and observed variables i.e. using the
icon. This icon simplifies the process of model construction. Click on that icon to draw the observed variables. After drawing it, the below image will appear.

Showing measurement error in the model
Lastly, one variable is used for denoting the measurement error or the error in the computation of the dataset. It is denoted by the
icon. It can be used for any observed and latent variable. After clicking it, draw the measurement error for the variables. The below image will appear.

Adding captions in the model
Lastly, add captions to the built model using the
icon.
Naming the variable in SPSS Amos interface
To name the variable, either double click on that variable or click on the object properties
icon and then select the variable to check. A new dialogue box will appear as shown below.

The ‘Variable name’ box defines the name present in the dataset while the ‘Variable label’ box is the specification for that variable. The dataset which was imported for representation had a variable named ‘VAR00036’ originally, as shown in the image above. However, to represent it as ‘AS1’ in the Amos diagram, it was changed in the ‘Variable label’ box to AS1.

To summarize all the variables that are included in the model,
icon is used.

Using arrows to show the direction of linkage between variables
The arrows in the Amos interface are used for stating the direction of linkage. There are two types of arrows; one each for linkage and covariance. The linkage between two variables is drawn using
icon.

Covariance i.e. joint variability of two variables is shown using the double-sided arrow, i.e. by using an icon.

Changing the build model
For changing the model, objects are selected using three different icons.
Selecting one object
For selecting only one object, the
icon is used. Herein, the selected object can be depicted by the blue highlighted line.

Selecting all objects
To select all objects icon
can be used. All of the selected items are represented in the below-shown figure.

Deselecting all objects
To deselect all the selected objects use
icon. With this, all the blue highlighted content will again be in its original form.
Duplicating an object
For duplicating an object or copying an object, use
icon. The duplicated object will be seen as shown below.

Moving an object in the Amos interface
Furthermore, to move the object, use
icon for moving the entire model
and
need to be selected together.
Deleting an object
To delete any object select
icon and click on the desired object.
Changing the size of a variable or object
The size adjustment of a variable or an object could be done using
icon. This icon would help in moving or resizing the object. In the below figure, we have enlarged the left rectangle.

Rotating a variable
Use the
icon to rotate the variable to the right by 90 degrees.

Miscellaneous icons related to the variable in Amos interface
Zoom in with
or zoom out with
, on the model.
To undo a step, click on
icon.
To redo a step, click on
icon.
To determine the variables defining a latent variable, use the
icon. When a model has too many latent variables, this icon helps to easily determine which observed variables are contributing to computing the latent one.
Lastly, to beautify the model and to make it visually appealing, click the icon
first, and then on the object. This will transform the model. Below is an example.

Output derivation in SPSS Amos interface
In Amos, the output of the model can be controlled by controlling the variables. For this, click on the analysis properties
icon.

‘Estimation’ helps to determine which type of estimation to compute i.e. maximum likelihood, generalized least square, or unweighted least squares.
The ‘Numerical’ option represents the type of numerical values required. Generally, negative covariance shows an error. Click on ‘Allow non-positive definite sample covariance matrices’ to perform the analysis.

Click on ‘Bias’ to adjust the type of bias or error in the model. It also allows selecting ‘Maximum likelihood’ or ‘Unbiased’ input and output.

Next, click on ‘Output’ to specify the output. There are multiple options to choose from as shown in the image below.

Lastly, bootstrapping allows the bootstrap of different results derived from ADF, GLS, SLS, or ULS models. It is used to duplicate the data multiple times and test it again.

Lastly, for computing the results, click on
icon and use
icon to view the output.
Summarized list of icons in SPSS Amos interface
All the icons of the Amos interface could be summarized in the below figure by stating the functions.

I am a management graduate with specialisation in Marketing and Finance. I have over 12 years' experience in research and analysis. This includes fundamental and applied research in the domains of management and social sciences. I am well versed with academic research principles. Over the years i have developed a mastery in different types of data analysis on different applications like SPSS, Amos, and NVIVO. My expertise lies in inferring the findings and creating actionable strategies based on them.
Over the past decade I have also built a profile as a researcher on Project Guru's Knowledge Tank division. I have penned over 200 articles that have earned me 400+ citations so far. My Google Scholar profile can be accessed here.
I now consult university faculty through Faculty Development Programs (FDPs) on the latest developments in the field of research. I also guide individual researchers on how they can commercialise their inventions or research findings. Other developments im actively involved in at Project Guru include strengthening the "Publish" division as a bridge between industry and academia by bringing together experienced research persons, learners, and practitioners to collaboratively work on a common goal.
I am a Senior Analyst at Project Guru, a research and analytics firm based in Gurugram since 2012. I hold a master’s degree in economics from Amity University (2019). Over 4 years, I have worked on worked on various research projects using a range of research tools like SPSS, STATA, VOSViewer, Python, EVIEWS, and NVIVO. My core strength lies in data analysis related to Economics, Accounting, and Financial Management fields.
Discuss