I have the relevant air sensor, it’d be really hard to blind it because it makes noise, and the behavioral effects thing is a good idea, thank you.
It’s not currently with me.
I think the next thing to do is build the 2.0 design, because it should perform better and will also be present with me, then test the empirical CO2 reduction and behavioral effects (although, again, blinding will be difficult), and reevaluate at that point.
I have the relevant air sensor, it’d be really hard to blind it because it makes noise, and the behavioral effects thing is a good idea, thank you.
Just randomizing would be useful; obviously, your air sensor doesn’t care in the least if it is ‘blinded’ or not. And if it’s placed in a room you don’t go into, that may be enough. As well, maybe you can modify it to have a flap or door or obstruction which opens or closes, greatly changing the rate of CO2 absorption, and randomize that; or if you have someone willing to help, they can come in every n time units to replace the filler or not, giving you both blinded & randomized comparisons between high-CO2-removal vs low-CO2-removal conditions based on whether they pulled out the used filler or not, since the fan presumably still makes the same noise regardless of whether it has brand-new filler removing CO2 at maximum rates or expired tired filler removing only a little CO2. (Remember, experiments work fine comparing 100% removal rates to, say, 10% removal rates; it doesn’t have to be exactly ‘on’/‘off’, that’s just a bit more statistically-efficient because it has a slightly larger effect size, and you have to remember the estimate is a bit lower than the ‘true’ estimate because the ‘off’ condition has 10% of the benefits of the ‘on’.)
I have the relevant air sensor, it’d be really hard to blind it because it makes noise, and the behavioral effects thing is a good idea, thank you.
It’s not currently with me.
I think the next thing to do is build the 2.0 design, because it should perform better and will also be present with me, then test the empirical CO2 reduction and behavioral effects (although, again, blinding will be difficult), and reevaluate at that point.
Just randomizing would be useful; obviously, your air sensor doesn’t care in the least if it is ‘blinded’ or not. And if it’s placed in a room you don’t go into, that may be enough. As well, maybe you can modify it to have a flap or door or obstruction which opens or closes, greatly changing the rate of CO2 absorption, and randomize that; or if you have someone willing to help, they can come in every n time units to replace the filler or not, giving you both blinded & randomized comparisons between high-CO2-removal vs low-CO2-removal conditions based on whether they pulled out the used filler or not, since the fan presumably still makes the same noise regardless of whether it has brand-new filler removing CO2 at maximum rates or expired tired filler removing only a little CO2. (Remember, experiments work fine comparing 100% removal rates to, say, 10% removal rates; it doesn’t have to be exactly ‘on’/‘off’, that’s just a bit more statistically-efficient because it has a slightly larger effect size, and you have to remember the estimate is a bit lower than the ‘true’ estimate because the ‘off’ condition has 10% of the benefits of the ‘on’.)