Here are three basic strategies to address this issue:

1. If there are variables which 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 list wise 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 non positive 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. Technote 1479694 provides an example of a Factor command that uses a correlation matrix as data. (That example uses MATRIX DATA commands to read the correlation matrix as text, but you could ignore the MATRIX DATA and focus on the FACTOR command, having created the matrix data file though MVA and OMS commands.

REF: http://www-01.ibm.com/support/docview.wss?uid=swg21480238

Thanks

There is no missing value. Sample size is 40,isn't it too small for factor analysis

Yes, the sample size is less than minimum. Please visit this link as it explains "The Minimum Sample Size in Factor Analysis very clearly"!

https://www.encorewiki.org/display/~nzhao/The+Minimum+Sample+Size+in+Factor+Analysis

Please checkout the answers to the same question on RG through:

https://www.researchgate.net/post/What_is_the_minimum_sample_size_for_factor_analysis

ıt means that all respondents answer your one of the items (at least) same answer thus there is no variability in that item for example all respondents answered The item 1 as 3 check item descriptive statistics you will see at least one item has zero standart deviation

Since there is no variability on that item/items , you can try to increase your sample size and hope some different answers for that items or you must delete that item/items.

the possible solutions are that.

thank you all