## 2 Materials and Methods
### Statistical Analysis  
The statistical analysis of the dataset was performed in four steps (Figure 1):  
1. Descriptive results were obtained.
2. The correlation between the available control and the perceived control using the Kruskal Wallis analysis of variance test was investigated [23; 42]. Groups with less than five individuals were not included in the analysis.
3. The relationship between the occupants' overall combined perceived control and the general physical building characteristics as well as the occupant personal characteristics was examined by applying a multilevel model [43; 44], to account for the three-level structure of our data (level 1-occupant, level 2-building, level 3-country). The ordered logistic regression analysis was applied using building and country as random effects and the covariates as fixed effects. Four step-by-step models were applied. The first was an empty model without any variable and with building and country variance only. In the second model, individual level variables were imported. The final version of the second model included variables, with \(p\)-value below 0.2, such as gender, age (in four groups, \(<\)35, 35-45, 46-55, \(>\)55), effort reward ratio, experience of negative events, use of air fresheners at home, type of job (managerial, professional, clerical/secretarial, other), type of job contract (full-time, part-time), and job contract duration (permanent, fixed-term). In the third model, building characteristics were imported iteratively on the second model to identify significant relations with the perceived control. Variables with a \(p\)-value below 0.2 were selected to be used in the next model. In the fourth model, both individual and building level variables were imported. The results of the fixed effects were reported in Odds Ratios (OR) and 95% Confidence Interval (CI). For the random effects, the explained variance is reported as well as the Proportional Change in Variance (PCV) between the null model and the final model with the variables.
4. The potential relations between the occupants' perceived control and perceived comfort and reported health symptoms (PSI5) were examined by using the spearman correlation [45]. This study focused on the correlation between the various combined control scores (e.g., perceived control over temperature and ventilation) and the perceived occupants' comfort. Additionally, the dependent variable (overall comfort satisfaction) and the response-variables were expressed in values on an ordinal scale; hence, ordinal regression analysis was employed to determine the impact of the controlling parameters on overall comfort. In the regression model, the response-dependent variable was the overall comfort satisfaction and the predictor-independent variables were the satisfaction for each personal controlling parameter as evaluated by the occupants. The results are presented in the format of OR and its CI95%. The ORs were used to rank the effect of the personal controlling parameters on overall comfort. \(p\)-values \(<\)0.05 were considered as statistically significant. The statistical package IBM SPSS Statistics [46] was used for the analysis.