Is there a maximum of this value that the dispersion is still reasonable.  ... View more

Maybe just a misunderstanding, because i thought with the other post that you were saying that there was no overdispersion, but maybe that are different problems. So, I thought you meant that the model did not look good.    I am content with the model, but I was just confused by the high value of the chi square/df ... View more

So, for my understanding. In this case the Chi-square/df does not really say something with this model. However, if you would use the poisson distribution. Like for instance this example. Only in this case, the chi-square/df says something? Is there an article about this?  The SAS System The GLIMMIX Procedure Model Information Data Set ANU.ORGANDAY1_3 Response Variable Progizz_score Response Distribution Poisson Link Function Log Variance Function Default Variance Matrix Blocked By Pen Estimation Technique Residual PL Degrees of Freedom Method Kenward-Roger Fixed Effects SE Adjustment Kenward-Roger Class Level Information Class Levels Values diet 2 1 2 strain 2 A B Number of Observations Read 60 Number of Observations Used 60 Dimensions R-side Cov. Parameters 1 Columns in X 9 Columns in Z per Subject 0 Subjects (Blocks in V) 30 Max Obs per Subject 3 Optimization Information Optimization Technique None Parameters 0 Lower Boundaries 0 Upper Boundaries 0 Fixed Effects Profiled Residual Variance Profiled Starting From Data Iteration History Iteration Restarts Subiterations Objective Function Change Max Gradient 0 0 0 -12.50422765 0.30362060 . 1 0 0 -9.527888119 0.00779297 . 2 0 0 -9.480642908 0.00000395 . 3 0 0 -9.480626779 0.00000000 . Convergence criterion (PCONV=1.11022E-8) satisfied. Fit Statistics -2 Res Log Pseudo-Likelihood -9.48 Generalized Chi-Square 7.82 Gener. Chi-Square / DF 0.14 Covariance Parameter Estimates Cov Parm Estimate Standard Error Residual (VC) 0.1397 0.02639 Type III Tests of Fixed Effects Effect Num DF Den DF F Value Pr > F diet 1 56 3.88 0.0539 strain 1 56 1.64 0.2059 diet*strain 1 56 0.81 0.3705 diet Least Squares Means diet Estimate Standard Error DF t Value Pr > |t| 1 1.1795 0.03708 56 31.81 <.0001 2 1.2829 0.03719 56 34.50 <.0001 strain Least Squares Means strain Estimate Standard Error DF t Value Pr > |t| A 1.1976 0.03886 56 30.82 <.0001 B 1.2648 0.03532 56 35.81 <.0001 diet*strain Least Squares Means strain diet Estimate Standard Error DF t Value Pr > |t| A 1 1.1221 0.05699 56 19.69 <.0001 B 1 1.2368 0.04746 56 26.06 <.0001 A 2 1.2730 0.05285 56 24.09 <.0001 B 2 1.2928 0.05233 56 24.70 <.0001   ... View more

Thank you for the explanation. However, the question arises. What are the other problems or is it better to use an entire different model, like proc mixed. ... View more