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IBM® SPSS® Amos™ is an easy-to-use structural equation modeling (SEM) program that tests relationships between observed and latent (unobserved) variables to quickly test hypotheses and confirm relationships.
If you are looking for a free trial of SPSS Amos, visit the SPSS Amos product page. Complete documentation for IBM SPSS AMOS 26.0 is available on the Knowledge Center
To download a product, go to the IBM Passport Advantage Online (PAO) and follow the instructions. Note, you must be an authorized user to log in. If you are not an authorized user, follow the instructions under “Request Access to PAO.'
After signing in to PAO and accepting the terms and conditions, navigate to the Software Download & Media Access tab.
Select the products using one of the following options:
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The required and optional parts for each product will be listed. Use the plus sign icon to expand the files in the download of your choice, or you can download each licensed eAssembly. Each eAssembly contains all of the required and optional downloads needed for a particular product and platform combination. SPSS Amos is only available for Windows and with 32-bit option.
If the product you downloaded requires an authorization or license code/key, log into the License Key Center to generate them. The License Key Center username/password is not the same as your Passport Advantage credentials. If you have forgotten your password or need to request access, follow the appropriate links on the License Key Center sign in page.
Any customer with an active support contract can seek activation assistance by logging a support request online at https://www.ibm.com/mysupport or by phone via links available at www.ibm.com/planetwide.
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The following table list all the product and part numbers available for IBM SPSS Amos 26.0:
[{'Business Unit':{'code':'BU053','label':'Cloud & Data Platform'},'Product':{'code':'SSLVC7','label':'SPSS Amos'},'Component':'--','Platform':[{'code':'PF033','label':'Windows'}],'Version':'26.0','Edition':','Line of Business':{'code':'LOB10','label':'Data and AI'}}]
Document Information
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