A comparison of fixed effect and mixed effect models in analyzing telecommunication products.

Mixed model is a model that combines fixed factors and random factors while fixed model is a model that only contains fixed factors. Observations made over time with the same object being observed are called repeated measurement. This research was conducted to determine the determinant factors of internet data quota sales which are influenced by SA (Sales Area), MC (Mutual Check), PC (Product Category), and time factors using a nested linear mixed model with repeated measurement and fixed model with repeated measurement. SA, PC, and time factors as fixed factors while the MC factor nested in SA as a random factor. The results showed that in nested linear mixed model with repeated measurement, the interaction effect between three fixed factors, namely between SA, PC, and time have a significant effect on the sales volume of internet data quota. In fixed model the analysis used the average value of internet data quota sales for each MC, so there is no interaction effect between three fixed factors in the fixed model. This shows that the fixed model is simpler than the mixed model. The nested mixed model with repeated measurement can better explain the effect of MC in SA because it includes random factors, namely the MC factor nested in SA. The fixed model with repeated measurement can better explain the effect of SA because SA is a fixed factor which is the average of MC. [ABSTRACT FROM AUTHOR]