The data analyst decided to run a five parameter multi-level linear model, using the same outcome variable Satisfaction, which measured guest satisfaction on a ten-point scale.  He now had five parameters in his model:  Satisfactionx (guest’ satisfaction with the hotel chain prior to them staying, measured on a ten-point scale); Sex (guests’ gender); Age (guests’ ages); Hotel (the 8 hotels in the chain); and Duration (measuring duration of each guest’s stay in days).  The log-likelihood for the five-parameter model was 1689.  How does this compare to his previous model?

A. The five parameter model is no better a fit than the previous one
B. The previous model was a better fit
C. The five parameter model is a better fit
D. Both models are flawed


Answer: C

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