I have an outcome variable
painRating which represents how painful a participant found a sensation. I can reasonably expect ratings to be affected by a painful stimulation. Thus I would like to run a mixed-effects model (lme4) to test that.
In my experiment I have various stimulation levels which were acquired individually for each participant ** but following a predetermined protocol **, thus I have limited and influenced the stimulation levels. Let's call my painful stimulation variable
stimulationValue. It is continuous numerical variable that ranges between 5 and 15.
In my understanding,
stimulationValue could be:
A) a random effect because the actual value of the stimulation is due to a participant variability (another random effect
participant) and whether or not a participant held a diagnosis (
diagnosis). So my model could look like:
painRating ~ diagnosis + (1 | stimulationValue) + (1 | diagnosis/participant)
B) a fixed effect because despite participant variability, I have limited the actual value to a range:
painRating ~ diagnosis + stimulationValue + (1 | diagnosis/participant)
Question: Am I wrong that 'stimulationValue' could be both a RE and a FE? If not, is there one way that I should choose over the other?
** If needed clarification - Before the experiment, I determined 6 various stimulation levels based on each participant's pain threshold and pain tolerance. Both measures differ between participants thus the resulting stimulation levels also differ.