Fase 2: Ventilation with Squared Meters
Stroom
9/7/2021
Exclusion on squared meters
Note below that we start excluding the group of stated surface area of home office, once it is above 100 Squared meters.
The effect of ventilation group on outcome metrics
In this part, we split our sample according to the distribution of the ventilation rate during the day. Note that we ask participants to rate the percentage of time they ventilate (either mechanical or physical) during the whole day. 100% equals the full day, 0% means not at all during the day.
Descriptives by Ventilation
Below you find the total descriptives and simple tests (categorical or nonparametric). We find income not to have an effect, but surface space does. Below we see a mean plot from which we can identify a fairly linear relationship between ventilation group and average surface. However, the differences in distribution are not abundantly clear.
| Low Ventilation (N=320) | Medium Ventilation (N=346) | High Ventilation (N=336) | Total (N=1002) | p value | |
|---|---|---|---|---|---|
| Percentage of Ventilation per day | < 0.001 (1) | ||||
| - Mean (SD) | 5.853 (4.167) | 34.725 (12.805) | 89.851 (12.974) | 43.990 (36.318) | |
| - Median (Q1, Q3) | 5.000 (1.000, 10.000) | 30.000 (25.000, 50.000) | 100.000 (80.000, 100.000) | 30.000 (10.000, 80.000) | |
| - Min - Max | 0.000 - 10.000 | 15.000 - 50.000 | 60.000 - 100.000 | 0.000 - 100.000 | |
| Job fit for WfH | 0.173 (1) | ||||
| - Mean (SD) | 7.616 (2.213) | 7.494 (2.419) | 7.679 (2.514) | 7.595 (2.387) | |
| - Median (Q1, Q3) | 8.000 (7.000, 9.000) | 8.000 (7.000, 9.000) | 8.000 (7.000, 10.000) | 8.000 (7.000, 10.000) | |
| - Min - Max | 1.000 - 10.000 | 1.000 - 10.000 | 1.000 - 10.000 | 1.000 - 10.000 | |
| Kids at Home | 0.159 (2) | ||||
| - Always | 15 (4.7%) | 10 (2.9%) | 8 (2.4%) | 33 (3.3%) | |
| - Sometimes | 95 (29.7%) | 128 (37.0%) | 110 (32.7%) | 333 (33.2%) | |
| - Never | 43 (13.4%) | 52 (15.0%) | 59 (17.6%) | 154 (15.4%) | |
| - No Kids | 167 (52.2%) | 156 (45.1%) | 159 (47.3%) | 482 (48.1%) | |
| - N-Miss | 0 | 0 | 0 | 0 | |
| Willingness to continue WfH | < 0.001 (1) | ||||
| - Mean (SD) | 5.797 (2.949) | 6.136 (2.930) | 6.792 (2.843) | 6.248 (2.933) | |
| - Median (Q1, Q3) | 6.500 (3.000, 8.000) | 7.000 (3.000, 8.000) | 7.000 (5.000, 9.000) | 7.000 (4.000, 9.000) | |
| - Min - Max | 1.000 - 10.000 | 1.000 - 10.000 | 1.000 - 10.000 | 1.000 - 10.000 | |
| WfH experience | 0.245 (2) | ||||
| - No | 89 (46.1%) | 95 (43.8%) | 113 (51.6%) | 297 (47.2%) | |
| - Yes | 104 (53.9%) | 122 (56.2%) | 106 (48.4%) | 332 (52.8%) | |
| - N-Miss | 127 | 129 | 117 | 373 | |
| Gender | 0.097 (2) | ||||
| - Male | 171 (53.4%) | 204 (59.0%) | 207 (61.6%) | 582 (58.1%) | |
| - Female | 149 (46.6%) | 142 (41.0%) | 129 (38.4%) | 420 (41.9%) | |
| - N-Miss | 0 | 0 | 0 | 0 | |
| opleiding | 0.083 (1) | ||||
| - Mean (SD) | 7.416 (2.859) | 7.101 (2.870) | 6.914 (2.816) | 7.139 (2.853) | |
| - Median (Q1, Q3) | 7.000 (5.000, 11.000) | 7.000 (4.000, 11.000) | 7.000 (4.000, 10.000) | 7.000 (4.000, 11.000) | |
| - Min - Max | 2.000 - 11.000 | 2.000 - 11.000 | 2.000 - 11.000 | 2.000 - 11.000 | |
| Age | 0.351 (1) | ||||
| - Mean (SD) | 43.144 (12.228) | 44.029 (13.235) | 44.464 (12.087) | 43.892 (12.539) | |
| - Median (Q1, Q3) | 44.000 (32.000, 53.000) | 44.000 (32.000, 56.000) | 45.000 (34.000, 54.000) | 44.000 (33.000, 54.000) | |
| - Min - Max | 20.000 - 67.000 | 19.000 - 67.000 | 20.000 - 68.000 | 19.000 - 68.000 | |
| Inkomen | 0.290 (1) | ||||
| - Mean (SD) | 3.972 (1.307) | 4.064 (1.268) | 4.134 (1.264) | 4.058 (1.279) | |
| - Median (Q1, Q3) | 4.000 (3.000, 5.000) | 4.000 (3.000, 5.000) | 4.000 (3.000, 5.000) | 4.000 (3.000, 5.000) | |
| - Min - Max | 1.000 - 6.000 | 1.000 - 6.000 | 1.000 - 6.000 | 1.000 - 6.000 | |
| Thuiskantoor m2 | 0.004 (1) | ||||
| - Mean (SD) | 23.139 (15.961) | 24.663 (17.213) | 27.545 (18.644) | 25.137 (17.400) | |
| - Median (Q1, Q3) | 20.000 (11.625, 32.000) | 20.000 (12.000, 35.000) | 24.000 (12.438, 36.000) | 20.000 (12.000, 35.000) | |
| - Min - Max | 3.000 - 90.000 | 4.000 - 90.000 | 2.000 - 98.000 | 2.000 - 98.000 | |
| - Missing | 12 | 18 | 16 | 46 | |
| Materieel ondersteuning | 0.355 (1) | ||||
| - Mean (SD) | 3.587 (1.434) | 3.737 (1.370) | 3.673 (1.522) | 3.668 (1.442) | |
| - Median (Q1, Q3) | 4.000 (3.000, 5.000) | 4.000 (3.000, 5.000) | 4.000 (2.000, 5.000) | 4.000 (3.000, 5.000) | |
| - Min - Max | 1.000 - 6.000 | 1.000 - 6.000 | 1.000 - 6.000 | 1.000 - 6.000 | |
| Tgenemoet onkosten | 0.426 (1) | ||||
| - Mean (SD) | 2.944 (1.764) | 3.081 (1.692) | 2.958 (1.750) | 2.996 (1.734) | |
| - Median (Q1, Q3) | 3.000 (1.000, 4.000) | 3.000 (1.000, 4.750) | 3.000 (1.000, 4.000) | 3.000 (1.000, 4.000) | |
| - Min - Max | 1.000 - 6.000 | 1.000 - 6.000 | 1.000 - 6.000 | 1.000 - 6.000 | |
| Immaterieel counseling e.d. | 0.077 (1) | ||||
| - Mean (SD) | 3.059 (1.464) | 3.301 (1.433) | 3.253 (1.510) | 3.208 (1.471) | |
| - Median (Q1, Q3) | 3.000 (2.000, 4.000) | 3.000 (2.000, 4.000) | 3.000 (2.000, 4.000) | 3.000 (2.000, 4.000) | |
| - Min - Max | 1.000 - 6.000 | 1.000 - 6.000 | 1.000 - 6.000 | 1.000 - 6.000 | |
| vrijheid voor eigen planning | 0.313 (1) | ||||
| - Mean (SD) | 3.819 (1.378) | 3.887 (1.284) | 3.988 (1.316) | 3.899 (1.326) | |
| - Median (Q1, Q3) | 4.000 (3.000, 5.000) | 4.000 (3.000, 5.000) | 4.000 (3.000, 5.000) | 4.000 (3.000, 5.000) | |
| - Min - Max | 1.000 - 6.000 | 1.000 - 6.000 | 1.000 - 6.000 | 1.000 - 6.000 |
- Kruskal-Wallis rank sum test
- Pearson’s Chi-squared test
Kruskal-Wallis rank sum test
data: clean\(surface by clean\)x Kruskal-Wallis chi-squared = 11.104, df = 2, p-value = 0.00388
Warning: Removed 484 rows containing non-finite values (stat_bin).
Correlations between independent and dependent variabeles.
Split the correlations by ventilation group
Two Way Manova’s
CBE at Home
We see that both ventilation as well as surface ar significant models, but no interaction (no interaction throughout). CBE1 to CBE4 translates to temperature, air, light and noise. Hence, both surface and ventilation are leading for Temperature, Air and Light, not noise.
[1] "General Manova Model - CBE at home" Df Pillai approx F num Df den Df Pr(>F)
(Intercept) 1 0.97075 7858.3 4 947 < 2.2e-16 ***
x 2 0.07812 9.6 8 1896 3.641e-13 ***
surface 1 0.02400 5.8 4 947 0.0001248 ***
x:surface 2 0.00967 1.2 8 1896 0.3254504
Residuals 950
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1[1] "simple effects" Response CBE_H1 :
Df Sum Sq Mean Sq F value Pr(>F)
(Intercept) 1 25074.1 25074.1 16081.5191 < 2.2e-16 ***
x 2 42.1 21.0 13.4969 1.660e-06 ***
surface 1 28.2 28.2 18.0996 2.304e-05 ***
x:surface 2 0.4 0.2 0.1248 0.8827
Residuals 950 1481.2 1.6
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Response CBE_H2 :
Df Sum Sq Mean Sq F value Pr(>F)
(Intercept) 1 27959.1 27959.1 23911.0730 < 2.2e-16 ***
x 2 74.0 37.0 31.6436 4.963e-14 ***
surface 1 9.7 9.7 8.3181 0.004014 **
x:surface 2 4.3 2.2 1.8565 0.156781
Residuals 950 1110.8 1.2
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Response CBE_H3 :
Df Sum Sq Mean Sq F value Pr(>F)
(Intercept) 1 27453.1 27453.1 19889.3108 < 2.2e-16 ***
x 2 69.7 34.8 25.2326 2.103e-11 ***
surface 1 19.7 19.7 14.2981 0.0001658 ***
x:surface 2 7.3 3.6 2.6321 0.0724539 .
Residuals 950 1311.3 1.4
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Response CBE_H4 :
Df Sum Sq Mean Sq F value Pr(>F)
(Intercept) 1 27463.8 27463.8 16205.6849 < 2.2e-16 ***
x 2 48.8 24.4 14.3903 6.969e-07 ***
surface 1 1.4 1.4 0.8257 0.3638
x:surface 2 2.1 1.0 0.6132 0.5418
Residuals 950 1610.0 1.7
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
484 observations deleted due to missingnessCBE at Work
We see that both ventilation as well as surface are insignificant models. Mild interaction at noise at work (multiple testing correction maybe)
[1] "General Manova Model - CBE at work" Df Pillai approx F num Df den Df Pr(>F)
(Intercept) 1 0.95686 5250.7 4 947 < 2e-16 ***
x 2 0.00387 0.5 8 1896 0.88455
surface 1 0.00045 0.1 4 947 0.98053
x:surface 2 0.01411 1.7 8 1896 0.09749 .
Residuals 950
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1[1] "simple effects" Response CBE_W1 :
Df Sum Sq Mean Sq F value Pr(>F)
(Intercept) 1 20076.5 20076.5 13030.6996 <2e-16 ***
x 2 2.9 1.5 0.9524 0.3862
surface 1 0.6 0.6 0.3839 0.5357
x:surface 2 3.3 1.6 1.0615 0.3463
Residuals 950 1463.7 1.5
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Response CBE_W2 :
Df Sum Sq Mean Sq F value Pr(>F)
(Intercept) 1 20287.9 20287.9 12567.4019 <2e-16 ***
x 2 1.5 0.7 0.4611 0.6307
surface 1 0.3 0.3 0.1604 0.6889
x:surface 2 0.8 0.4 0.2354 0.7903
Residuals 950 1533.6 1.6
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Response CBE_W3 :
Df Sum Sq Mean Sq F value Pr(>F)
(Intercept) 1 24473.4 24473.4 14504.7062 <2e-16 ***
x 2 0.9 0.4 0.2587 0.7721
surface 1 0.1 0.1 0.0772 0.7812
x:surface 2 1.7 0.8 0.5005 0.6064
Residuals 950 1602.9 1.7
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Response CBE_W4 :
Df Sum Sq Mean Sq F value Pr(>F)
(Intercept) 1 20426.3 20426.3 11398.3472 < 2.2e-16 ***
x 2 4.3 2.1 1.1918 0.304123
surface 1 0.4 0.4 0.2090 0.647665
x:surface 2 17.6 8.8 4.9091 0.007567 **
Residuals 950 1702.4 1.8
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
484 observations deleted due to missingnessHWC at Home
For these levels of satisfaction, only ventilation matters: surface is only mildy significant for chair satisfaction (other categories are desk (1), Screen(3), hardware, and wifi). WIfi shows a light interaction satisfaction.
[1] "General Manova Model - HWC at home" Df Pillai approx F num Df den Df Pr(>F)
(Intercept) 1 0.95631 4140.9 5 946 < 2.2e-16 ***
x 2 0.07622 7.5 10 1894 8.346e-12 ***
surface 1 0.00860 1.6 5 946 0.1463
x:surface 2 0.01708 1.6 10 1894 0.0919 .
Residuals 950
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1[1] "simple effects" Response HWC_H1 :
Df Sum Sq Mean Sq F value Pr(>F)
(Intercept) 1 18469.5 18469.5 8065.2146 < 2.2e-16 ***
x 2 89.3 44.6 19.4967 5.033e-09 ***
surface 1 12.6 12.6 5.4867 0.01937 *
x:surface 2 5.2 2.6 1.1278 0.32416
Residuals 950 2175.5 2.3
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Response HWC_H2 :
Df Sum Sq Mean Sq F value Pr(>F)
(Intercept) 1 19224.2 19224.2 7960.3610 < 2.2e-16 ***
x 2 108.7 54.4 22.5055 2.821e-10 ***
surface 1 6.6 6.6 2.7264 0.09903 .
x:surface 2 5.2 2.6 1.0835 0.33883
Residuals 950 2294.2 2.4
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Response HWC_H3 :
Df Sum Sq Mean Sq F value Pr(>F)
(Intercept) 1 22559.3 22559.3 9881.7894 < 2.2e-16 ***
x 2 61.7 30.8 13.5060 1.645e-06 ***
surface 1 6.0 6.0 2.6424 0.1044
x:surface 2 2.2 1.1 0.4772 0.6207
Residuals 950 2168.8 2.3
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Response HWC_H4 :
Df Sum Sq Mean Sq F value Pr(>F)
(Intercept) 1 25630.2 25630.2 15211.6991 < 2.2e-16 ***
x 2 83.6 41.8 24.8200 3.112e-11 ***
surface 1 2.2 2.2 1.2957 0.2553
x:surface 2 3.3 1.6 0.9765 0.3770
Residuals 950 1600.7 1.7
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Response HWC_H5 :
Df Sum Sq Mean Sq F value Pr(>F)
(Intercept) 1 26108.8 26108.8 15531.6214 < 2.2e-16 ***
x 2 51.7 25.9 15.3860 2.654e-07 ***
surface 1 0.4 0.4 0.2298 0.63181
x:surface 2 14.1 7.1 4.2009 0.01526 *
Residuals 950 1597.0 1.7
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
484 observations deleted due to missingnessHWC at Home
For these levels of satisfaction, no models seem to be significant. Simple effects do show, but must be interpreted with caution: even then, ventilation is leading.
[1] "General Manova Model - HWC at work" Df Pillai approx F num Df den Df Pr(>F)
(Intercept) 1 0.97438 7195.5 5 946 <2e-16 ***
x 2 0.01734 1.7 10 1894 0.0856 .
surface 1 0.00898 1.7 5 946 0.1287
x:surface 2 0.00491 0.5 10 1894 0.9124
Residuals 950
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1[1] "simple effects" Response HWC_W1 :
Df Sum Sq Mean Sq F value Pr(>F)
(Intercept) 1 28655.6 28655.6 23640.1433 < 2.2e-16 ***
x 2 11.8 5.9 4.8529 0.008001 **
surface 1 0.8 0.8 0.6370 0.424984
x:surface 2 0.3 0.2 0.1278 0.880066
Residuals 950 1151.6 1.2
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Response HWC_W2 :
Df Sum Sq Mean Sq F value Pr(>F)
(Intercept) 1 27689.4 27689.4 22006.4772 < 2e-16 ***
x 2 6.5 3.2 2.5666 0.07733 .
surface 1 2.1 2.1 1.6308 0.20190
x:surface 2 1.8 0.9 0.7184 0.48782
Residuals 950 1195.3 1.3
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Response HWC_W3 :
Df Sum Sq Mean Sq F value Pr(>F)
(Intercept) 1 29139.4 29139.4 24603.5354 < 2e-16 ***
x 2 10.5 5.2 4.4230 0.01225 *
surface 1 0.0 0.0 0.0390 0.84339
x:surface 2 0.9 0.5 0.3873 0.67897
Residuals 950 1125.1 1.2
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Response HWC_W4 :
Df Sum Sq Mean Sq F value Pr(>F)
(Intercept) 1 28251.9 28251.9 25387.7897 < 2.2e-16 ***
x 2 11.3 5.7 5.0916 0.006317 **
surface 1 0.2 0.2 0.1667 0.683130
x:surface 2 2.4 1.2 1.0859 0.338018
Residuals 950 1057.2 1.1
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Response HWC_W5 :
Df Sum Sq Mean Sq F value Pr(>F)
(Intercept) 1 29150.5 29150.5 22213.6194 < 2.2e-16 ***
x 2 13.7 6.8 5.2147 0.005593 **
surface 1 0.0 0.0 0.0242 0.876459
x:surface 2 0.2 0.1 0.0594 0.942374
Residuals 950 1246.7 1.3
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
484 observations deleted due to missingness