Typically when reporting test results from a GLM I use the format
(F(df_factor_term,df_error_term)=Fstat, p=pvalue), i.e., (F(n,n1)=statistic,p=pvalue). My question is what is the equivalent format for a reporting results from a linear mixed model. For example if I have a fixed effect for term X SPSS outputs numerator and denominator degrees of freedom(df), I am assuming that F(df_numerator,df_denominator) is equivalent to F(df_factor_term,df_error_term), and in both instances the significance level for the F is from the F distribution with the degrees of freedom for the numerator and denominator mean squares. If that is correct, why does the denominator df in the mixed model not take on the value of n1(or some constant, where n=number of factor levels)? Thanks in advance for your comments.  K.  Kambiz Tavabi PhD Biomedical Imaging Laboratory The Children's Hospital of Philadelphia 34th Street and Civic Center Boulevard Philadelphia, Pa. 19104 Tel: 267.426.0302  ===================== To manage your subscription to SPSSXL, send a message to [hidden email] (not to SPSSXL), with no body text except the command. To leave the list, send the command SIGNOFF SPSSXL For a list of commands to manage subscriptions, send the command INFO REFCARD 
The denominator df are computed using Satterthwaite's approximation. More details are in the MIXED algorithms documentation (Help > Algorithms). Alex
Typically when reporting test results from a GLM I use the format (F(df_factor_term,df_error_term)=Fstat, p=pvalue), i.e., (F(n,n1)=statistic,p=pvalue). My question is what is the equivalent format for a reporting results from a linear mixed model. For example if I have a fixed effect for term X SPSS outputs numerator and denominator degrees of freedom(df), I am assuming that F(df_numerator,df_denominator) is equivalent to F(df_factor_term,df_error_term), and in both instances the significance level for the F is from the F distribution with the degrees of freedom for the numerator and denominator mean squares. If that is correct, why does the denominator df in the mixed model not take on the value of n1(or some constant, where n=number of factor levels)? Thanks in advance for your comments.  K. 
In reply to this post by Kambiz
Thanks Alex. So is it safe to say that
the mixed model, and how the df (apparently related to a covariance
matrix) is computed, is a nonparametric alternative to the GLM?
Such that there is no assumption that the underlying population variances are
equally distributed.And so the denominator value is the effective df for
the chisqure distribution of the linear combination of sample variances? I am
just trying to put in words the equations in the algorithm.
 Original Message 

Satterthwaite is not a nonparametric method, but it is robust under unequal variances... however, I would think it would be better to incorporate the heteroscedastic variances directly into the model. In a really simple scenario, look at the salesperformance.sav dataset that ships with the product and run the following syntax. The first MIXED command fits a model that assumes equal variances across the categories of the grouping variable, while the second MIXED command fits a separate residual variance parameter for each group. COMPUTE case = $casenum. MIXED perform BY group /FIXED=group /PRINT=R SOLUTION TESTCOV. MIXED perform BY group /FIXED=group /PRINT=R SOLUTION TESTCOV /REPEATED=group  SUBJECT(case) COVTYPE(DIAG). Alex
Thanks Alex. So is it safe to say that the mixed model, and how the df (apparently related to a covariance matrix) is computed, is a nonparametric alternative to the GLM? Such that there is no assumption that the underlying population variances are equally distributed.And so the denominator value is the effective df for the chisqure distribution of the linear combination of sample variances? I am just trying to put in words the equations in the algorithm.  Original Message  From: Alex Reutter Sent: Friday, July 23, 2010 12:17 PM Subject: Re: Mixed model ANOVA degrees of freedom The denominator df are computed using Satterthwaite's approximation. More details are in the MIXED algorithms documentation (Help > Algorithms). Alex
Typically when reporting test results from a GLM I use the format (F(df_factor_term,df_error_term)=Fstat, p=pvalue), i.e., (F(n,n1)=statistic,p=pvalue). My question is what is the equivalent format for a reporting results from a linear mixed model. For example if I have a fixed effect for term X SPSS outputs numerator and denominator degrees of freedom(df), I am assuming that F(df_numerator,df_denominator) is equivalent to F(df_factor_term,df_error_term), and in both instances the significance level for the F is from the F distribution with the degrees of freedom for the numerator and denominator mean squares. If that is correct, why does the denominator df in the mixed model not take on the value of n1(or some constant, where n=number of factor levels)? Thanks in advance for your comments.  K. 
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