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I'm performing an experiment with five main effects resp. 6-7 since these main effects influences are studied on 20 sensors (which can be grouped into 3 manufacturers). The design is

    Temperature [°C] Rel. Humidity [%]  Hydrogen [ppm]  Carbon_monoxide [ppm]   Ethen[ppm]
50  30  250 250 50
18  11  100 100 100
18  11  500 500 100
18  11  100 500 25
18  11  500 100 25
70  11  100 500 100
70  11  500 500 25
70  11  100 100 25
70  11  500 100 100
50  30  250 250 50
18  84  500 100 100
18  84  100 500 100
18  84  100 100 25
18  84  500 500 25
70  84  500 500 100
70  84  100 100 100
70  84  100 500 25
70  84  500 100 25
50  30  250 250 50

Now, how can I determine which effects are significant and also which interactions and how do they effect the response of the sensors? At the moment I'm trying to model the relationship like given here in How to use multiple variables in a mixed model? Given I find the correct or most meaningful relationship: What's next?

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  • $\begingroup$ What is the response variable? $\endgroup$
    – Mickybo Yakari
    Commented Jan 16, 2020 at 10:36
  • $\begingroup$ The response variable is the resistance of the sensors (each sensor has its own individual response). $\endgroup$
    – Ben
    Commented Jan 16, 2020 at 10:37
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    $\begingroup$ Given that this is experimental, I am assuming you are able to collect data such that you have a balanced design (equal sample sizes in each cell of the combinations of the five factors). If that is the case, a multiway ANOVA may be easier to implement. It should, however, produce results that agree with a mixed-effects model. Be planful regarding the higher-order interactions (e.g., 3-way, 4-way, and 5-way). I would recommend only include those you have some reason to believe may be meaingful (they are difficult to interpret). $\endgroup$
    – dbwilson
    Commented Jan 21, 2020 at 14:43
  • $\begingroup$ Thanks, but how do I determine/evaluate whether an effect is significant or meaningful in general? $\endgroup$
    – Ben
    Commented Jan 21, 2020 at 14:59

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