This error occurs when you have used an incorrect character in naming the variables. Also, you should not use Persian or Arabic words in naming the variables.

Be careful in naming the latent variables and not choose a name that is available in the SPSS data file. For example, if a variable or a column named “IPW” in data exists, it should not name one of the hidden variables as “IPW.” On the other hand, the variable names in the data file with the naming of the latent variables in the AMOS model should be distinct and not repeated.

Amos’ software cannot run the model with a dataset that includes some missing values, and the following error occurs. It is also better to estimate missing data using standard methods before importing data into AMOS software. Also, if the number of missing data is small, you can delete the participant with missed information. Finally, if your data still has missing data, do the following to fix the problem:
1- From the AMOS tools section, select Analysis properties.
2- In the window opened through the Estimation page, activate the Estimate means and intercept option.

Sometimes variables in the data file have a very high correlation. The existence of these variables causes the collinearity and non-reversibility of the data matrix to estimate the model. As a result, the error appears, and the model does not run. It also happens that when entering data into SPSS or Excel software and during the data management stage, the information related to a column or variable is mistakenly repeated twice. For example, in the data file, there may be at least two variables whose numbers are the same for each cell or are a linear combination of each other. If there is such data, the model does not run, and the above error appears. 

Note: Another reason for this error is the small sample size.
Solution: Using the Correlate command in SPSS, get the correlation coefficient between all the obvious variables of the report. Look for variables that have a correlation coefficient higher than 0.85. If there are such variables, check the accuracy of the data. If you find two variables that have a correlation coefficient higher than 0.85, you should enter one of these two variables in the model.

When several independent variables are in the structural equation model in AMOS software, it Must determine whether these independent variables are related or not. Therefore, this warning appears to draw covariances. If the independent variables are unrelated, click on Proceed with the analysis option and run the model.

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