Sarah Crosby (PhD Candidate, BDRG) has done an excellent study of applying Bayesian inference to examine the possible quantifiable correlation that can be struck between perceived thermal comfort of office occupants and the non-thermal conditions of the environment around them. A link to the paper here, and our abstract:

The judgment of thermal comfort is a cognitive process influenced by physical, psychological and other factors. Prior studies have suggested that occupants who are generally satisfied with many non-thermal conditions of indoor environmental quality (IEQ) are also more likely to be satisfied with thermal conditions as well. This paper applies Bayesian logistic regression to identify and predict the independent relationship between non-thermal metrics of IEQ, such as CO₂ concentrations, noise levels, and light levels, and perceived thermal comfort. The study is the first to do so with respect to a large field study. The regression analysis is done against a dataset of objective and subjective IEQ measurements collected from 779 occupants of open-plan offices in large Canadian and US cities. The results suggest there is evidence supporting a view that measurements of indoor CO₂ concentrations and indoor speech intelligibility are correlated with perceived thermal satisfaction. For example, a posteriori predictions drawn from the regression model suggest that, under the same psychrometric conditions (i.e., operative temperature = 23 °C, relative humidity = 30%, etc.), occupants experiencing indoor CO₂ concentrations of 500 ppm were ~30 ± 8% more likely to state they felt thermally satisfied than occupants experiencing indoor conditions at 900 ppm.

Crosby, S., Rysanek, A. (2020). Correlations between thermal satisfaction and non-thermal conditions of indoor environmental quality: Bayesian inference of a field study of offices. Journal of Building Engineering, 102051.