Suppose we consider a model with an interaction term as well as a x 1 2 term. Be

Question

Suppose we consider a model with an interaction term as well as a x12 term. Below is the R output for this model. Use the nested models test to see if the interaction term and x12 term can be dropped from the model.

Analysis of Variance Source Sum of Squares Square DF Mean F Value Pr>F Model Error Corrected Total 19 1680.80000 4 1505.20106 376.3002632.14 Estimate Error Intercept 1 38.07465 3.88036 9.81 .0001 0.047301.90 0.0770 7.890643.878882.03 0.0600 sizetvpe1 0.00097261 0.01964 0.05 0.9612 1 -0.00003474 0.000134410.26 0.7996 size 1-0.08981 size2

Explanation / Answer

Here the third table gives the results corresponding to t test for individual variable.

For intercept, the corresponding p-value is <0.0001, hence we can conclude that the intercept is significant and should not dropped from the model.

The p-values corresponding to size and type are 0.0770 and 0.0600 respectively which is greater than 0.05 and less than 0.1. We can conclude that the size and type are not siznificant at 5% level of significance and we should remove those from the model, on the other hand, if we consider 10% level of significance, these terms can still kept in the model.

The p-value corresponding to interaction sizetype is 0.9612 which is greater than 0.05, hence we can conclude that the interaction term should be dropped from the model. Similarly p-value for size2 is 0.7996 which is again greater than 0.05, hence we can drop Size2 as well.

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