# The number of degrees of freedom (0) is not positive. Factor analysis may not be appropriate.

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## The number of degrees of freedom (0) is not positive. Factor analysis may not be appropriate.

 This post has NOT been accepted by the mailing list yet. I am trying to do a factor analysis with 3 variables (11 point response scale) and 220 cases but am getting an error message and no idea why: The number of degrees of freedom (0) is not positive. Factor analysis may not be appropriate. Can anyone help me figure out why? ps I get a similar message when i try to do it in MPlus
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## Re: The number of degrees of freedom (0) is not positive. Factor analysis may not be appropriate.

 Administrator You would do much better to post your syntax. Degrees of freedom are NOT typically relevant in most applications of EFA in SPSS. Are you perhaps using AMOS and mispecifying your model? If so then review some basic texts about minimal requirements for model identification. CC wrote I am trying to do a factor analysis with 3 variables (11 point response scale) and 220 cases but am getting an error message and no idea why: The number of degrees of freedom (0) is not positive. Factor analysis may not be appropriate. Can anyone help me figure out why? ps I get a similar message when i try to do it in MPlus Please reply to the list and not to my personal email. Those desiring my consulting or training services please feel free to email me. --- "Nolite dare sanctum canibus neque mittatis margaritas vestras ante porcos ne forte conculcent eas pedibus suis." Cum es damnatorum possederunt porcos iens ut salire off sanguinum cliff in abyssum?"
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## Re: The number of degrees of freedom (0) is not positive. Factor analysis may not be appropriate.

 In reply to this post by CC Are there missing data? What are your 3 variables? What are  3 correlation coefficients? 1 vs 2, 1 vs 3, 2 vs 3? What is your syntax? What is the purpose of the factor analysis? If you do a 3D scatterplot, does anything look oddball? Do your 2 variables add up to a constant? Art Kendall Social Research Consultants
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## Re: The number of degrees of freedom (0) is not positive. Factor analysis may not be appropriate.

 This post has NOT been accepted by the mailing list yet. In reply to this post by David Marso Thanks for your response.  I'm using SPSS rather than amos. This is the syntax: DATASET ACTIVATE DataSet1. FACTOR   /VARIABLES Dg4 Dg5 Dg6   /MISSING LISTWISE   /ANALYSIS Dg4 Dg5 Dg6   /PRINT INITIAL KMO EXTRACTION ROTATION   /FORMAT SORT   /PLOT EIGEN   /CRITERIA MINEIGEN(1) ITERATE(25)   /EXTRACTION ML   /CRITERIA ITERATE(25) DELTA(0)   /ROTATION OBLIMIN.
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## Re: The number of degrees of freedom (0) is not positive. Factor analysis may not be appropriate.

 This post has NOT been accepted by the mailing list yet. In reply to this post by Art Kendall Hi Thanks for your response. The three variables are attitude questions.  I am trying to see if they load onto the same factor in order to establish if I can sum them to form an attitude scales. There are some missing data but not very much. These are the correlations between the variables: Correlations                 Dg4 Dg5 Dg6 Dg4 Pearson Correlation 1 .578** .719**         Sig. (2-tailed) .000 .000         N 220 220 220 Dg5 Pearson Correlation .578** 1 .720**         Sig. (2-tailed) .000 .000         N 220 220 220 Dg6 Pearson Correlation .719** .720** 1         Sig. (2-tailed) .000 .000         N 220 220 220 ** Correlation is significant at the 0.01 level (2-tailed). Thanks
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## Re: The number of degrees of freedom (0) is not positive. Factor analysis may not be appropriate.

 Do you have different sets of items that are intended to measure different constructs? I.e., these three items are intended to measure one attitude construct and there are other set of items meant to measure others? If that is so why not put all of the items for all of the constructs into one analysis? if you are constructing  scales why would you not use varimax rotation? If there is only one attitude construct, I suggest you use RELIABILITY to look at the internal consistency. When you do the 3D scatterplot what do you see? Art Kendall Social Research Consultants
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## Re: The number of degrees of freedom (0) is not positive. Factor analysis may not be appropriate.

 Administrator In reply to this post by CC While the formula for df is not spelled out in the algorithms document I suspect it is something along the lines of p*(p-1)/2-k where p is the number of variables, k is the number of estimated parameters (loadings).  That would yield 0 df with a 3 variable analysis.  Inspection of 3, 4, and 5 variable simulations bears out my conjecture. CC wrote Thanks for your response.  I'm using SPSS rather than amos. This is the syntax: DATASET ACTIVATE DataSet1. FACTOR   /VARIABLES Dg4 Dg5 Dg6   /MISSING LISTWISE   /ANALYSIS Dg4 Dg5 Dg6   /PRINT INITIAL KMO EXTRACTION ROTATION   /FORMAT SORT   /PLOT EIGEN   /CRITERIA MINEIGEN(1) ITERATE(25)   /EXTRACTION ML   /CRITERIA ITERATE(25) DELTA(0)   /ROTATION OBLIMIN. Please reply to the list and not to my personal email. Those desiring my consulting or training services please feel free to email me. --- "Nolite dare sanctum canibus neque mittatis margaritas vestras ante porcos ne forte conculcent eas pedibus suis." Cum es damnatorum possederunt porcos iens ut salire off sanguinum cliff in abyssum?"
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## Re: The number of degrees of freedom (0) is not positive. Factor analysis may not be appropriate.

 This post has NOT been accepted by the mailing list yet. In reply to this post by Art Kendall Thanks for your response I have done reliability analysis. Alpha reliability is .86. Yes there are other items to measure other constructs but I'm building up the model gradually. I'm not using varimax because i don't expect all factors to be orthogonal I haven't done a plot - to be honest I wouldn't know what to look for. Have you any idea why this message is coming up?
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## Re: The number of degrees of freedom (0) is not positive. Factor analysis may not be appropriate.

 This post has NOT been accepted by the mailing list yet. In reply to this post by David Marso Thanks for your comment David. Can you explain what you mean? - Im not sure I follow what you are saying? And what do you suggest i need to do to get the factor analysis to run?
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## Re: The number of degrees of freedom (0) is not positive. Factor analysis may not be appropriate.

 Administrator This post was updated on . There is really nothing to explain that isn't clearly specified in my comment. Basically 3-3=0! Why are you using Maximum Likelihood extraction in the first place? If you insist on using ML with only 3 variables you will get precisely this error/warning message. Perhaps curl up with a decent book on factor analysis before pressing onward. -- CC wrote Thanks for your comment David. Can you explain what you mean? - Im not sure I follow what you are saying? And what do you suggest i need to do to get the factor analysis to run? Please reply to the list and not to my personal email. Those desiring my consulting or training services please feel free to email me. --- "Nolite dare sanctum canibus neque mittatis margaritas vestras ante porcos ne forte conculcent eas pedibus suis." Cum es damnatorum possederunt porcos iens ut salire off sanguinum cliff in abyssum?"
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## Re: The number of degrees of freedom (0) is not positive. Factor analysis may not be appropriate.

 This post has NOT been accepted by the mailing list yet. Perhaps but I am an spss user rather than a statistician so don't really follow what you mean Plus i have done factor analyses with only 3 variables before (expecting a single factor solution) and it worked fine so I am wondering why it would be different in this instance?
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## Re: The number of degrees of freedom (0) is not positive. Factor analysis may not be appropriate.

 In reply to this post by David Marso Unless you have an unusually advanced knowledge of factor analysis, for scale construction I suggest that you use the traditional principal axes extraction and varimax rotation. Principal axes because you would only be interested in the common variance across the items. Varimax rotation because you want your final measures to have divergent validity from each other. How many attitude constructs do you have in your data?  How did you decide to have only 3 items to measure a construct? Have these items been used to measure these constructs in previous research? How many items are there combined for all of the constructs? What is your listwise N across all of the items? Art Kendall Social Research Consultants
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## Re: The number of degrees of freedom (0) is not positive. Factor analysis may not be appropriate.

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## Re: The number of degrees of freedom (0) is not positive. Factor analysis may not be appropriate.

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## Re: The number of degrees of freedom (0) is not positive. Factor analysis may not be appropriate.

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## Re: The number of degrees of freedom (0) is not positive. Factor analysis may not be appropriate.

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## Re: The number of degrees of freedom (0) is not positive. Factor analysis may not be appropriate.

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## Re: The number of degrees of freedom (0) is not positive. Factor analysis may not be appropriate.

 In reply to this post by David Marso Just a couple of points: (1) If I am not mistaken, the general formula for degrees of freedom in factor analysis is df=  [(p - k}^2 - (p + k)]/2 where p = number of empirical variable and k = number of factors. (see http://tinyurl.com/google-FA-df ) If one has 3 empirical variables and assumes that there is only one general factor, then df= [(3 - 1)^2 - (3 + 1)]/2 = [(2)^2 - 5]/2 = [4 - 4]/2 df = 0/2 = 0 A situation with df=0 means that that the model (here, a single factor) is "just identified".  You can get a solution but it is not unique.  That is, the loading of variables on the factors, the variances and covariances, are not uniquely determined. A confirmatory factor analysis would require you to set constraints on these (e.g., all loadings are equal, etc.). But this would not explain why you got an error message saying that you have negative degrees of freedom. (2) I'm inferring from your syntax (provided below), that SPSS extracted 2 factors.  If it did then the df df= [(3 -2)^2 - (3 + 2)]/2 = [1 - 5]/2 = -2 The OP's use of mineigen(1) means that all factors with eigenvalue greater than 1 will used and the presence of a ROTATION command implies that at least 2 factors are present -- one doesn't rotate a single factor. If the OP doesn't want to do a CFA,  let me suggest the following substitutions: /criteria=factors(1) (extract only one factor) and /rotation norotate. (don't even think of rotating the solution) SPSS' factor doesn't do confirmatory factor analysis but you can determine how well certain models fit but only in a very limited way.  AMOS will do CFA but one has to really know what their measurement model is.  The OP should take a look at the following article, not because it provide you a solution to his situation but as a starting point to the issues he will have to deal with: http://journals.sagepub.com/doi/abs/10.1177/0013164412457367?journalCode=epma-Mike Palij New York University [hidden email] > DATASET ACTIVATE DataSet1. > FACTOR >   /VARIABLES Dg4 Dg5 Dg6 >   /MISSING LISTWISE >   /ANALYSIS Dg4 Dg5 Dg6 >   /PRINT INITIAL KMO EXTRACTION ROTATION >   /FORMAT SORT >   /PLOT EIGEN >   /CRITERIA MINEIGEN(1) ITERATE(25) >   /EXTRACTION ML >   /CRITERIA ITERATE(25) DELTA(0) >   /ROTATION OBLIMIN. ----- Original Message ----- On Thursday, May 18, 2017 5:30 PM, David Marso wrote; > There is really nothing to explain that isn't clearly specified in my > comment. > Basically 3-3=0! > Why are you using Maximum Likelihood extraction in the first place? > If you insist on using ML with only  variables you will get precisely > this > error/warning message. > Perhaps curl up with a decent book on factor analysis before pressing > onward. > -- > > CC wrote >> Thanks for your comment David. >> Can you explain what you mean? - Im not sure I follow what you are >> saying? >> And what do you suggest i need to do to get the factor analysis to >> run? ===================== To manage your subscription to SPSSX-L, send a message to [hidden email] (not to SPSSX-L), with no body text except the command. To leave the list, send the command SIGNOFF SPSSX-L For a list of commands to manage subscriptions, send the command INFO REFCARD
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