Lack of fit in rsm

[RonaKurian]

I am using response surface analysis with four factors using box behnken design but the lack of fit test is becoming significant.
Response: Cognitive_Demand
Df Sum Sq Mean Sq F value Pr(>F)
FO(x1, x2, x3, x4) 4 0.198030 0.049508 2.1970e+03 6.208e-07
TWI(x1, x2, x3, x4) 6 0.012877 0.002146 9.5245e+01 0.0002872
PQ(x1, x2, x3, x4) 4 0.002209 0.000552 2.4508e+01 0.0044902
Residuals 4 0.000090 0.000023
Lack of fit 1 0.000090 0.000090 4.6801e+29 < 2.2e-16
Pure error 3 0.000000 0.000000
How can I address this issue? how to solve the problem

[williaml]

Hi, can you provide a reproducible example?

FAQ: How to do a minimal reproducible example ( reprex ) for beginners

A minimal reproducible example consists of the following items: A minimal dataset, necessary to reproduce the issue The minimal runnable code necessary to reproduce the issue, which can be run on the given dataset, and including the necessary information on the used packages. Let's quickly go over each one of these with examples: Minimal Dataset (Sample Data) You need to provide a data frame that is small enough to be (reasonably) pasted on a post, but big enough to reproduce your issue. Let's say, as an example, that you are working with the iris data frame head(iris) #> Sepal.Length Sepal.Width Petal.Length Petal.Width Species #> 1 5.1 3.5 1.4 0.…