EFA_Query

[ANKITA BHATIA]

Dear Neeraj Sir and Scholars.

While performing EFA, I am getting the following error in SPSS Output. Below is the screenshot.

What does this mean? Also I checked standard deviations item wise to check for zero variance, and none of my items had zero variance means unengaged response. Just to note that I have 48 questions and I entered all together. Please help me on this.

Regards,

Ankita

[Raja Sankaran]

Dear Ankita,

Here are three basic strategies to address the issue related to the error message "Factor Analysis returns error that there are fewer than 2 cases, variable with 0 variance, or only 1 variable". Do let me know if this was useful.

1. If there are variables that have particularly high rates of missing values, drop these variables and see if this improves the retention of cases. If you have the 'Missing Value Analysis' module, this can be very helpful in seeing patterns of missing values (4000 cases are missing on var21, var40, and var50, for example). If you have MVA installed, you will see a "Missing Value Analysis" option near the bottom of the Analyze menu in SPSS.

2. Pairwise deletion. By default, Factor uses listwise deletion of cases with missing values, i.e. a case is omitted from the analysis if it is missing on any of the variables in the Factor variable list. With pairwise deletion, each correlation is computed from all cases that are non-missing on those 2 respective variables, without regard to their 'missingness' on the other variables in the list. You can choose pairwise deletion from the Options dialog in Factor and this may get you around the problem. However, there can be numerical problems that result from pairwise deletion (such as nonpositive definite correlation matrices) and biases in the resulting solutions.

3. If you have the SPSS Missing Value Analysis (MVA) module, then you can use the MVA procedure to estimate a covariance matrix for the data that uses all of the data that is present. MVA can estimate this matrix with either the Regression method or the EM method (Expectation, Maximization, based on the work of Little & Rubin ). You can then use this covariance matrix as input to the Factor procedure.

 

Regards

Raja Sankaran

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[ANKITA BHATIA]

Dear Raja Sir,

Many Thanks for the input. I applied missing value analysis as advised by you in point no 3 and I was able to get the output.

Once again Thankyou Sir. 

Regards,

Ankita

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