Implementation of multivariate linear mixed-effects models in the analysis of indoor climate performance experiments
Publication: Research - peer-review › Journal article – Annual report year: 2011
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Implementation of multivariate linear mixed-effects models in the analysis of indoor climate performance experiments. / Jensen, Kasper Lynge; Spliid, Henrik; Toftum, Jørn.
In: International Journal of Biometeorology, Vol. 56, No. 1, 2011, p. 129-136.Publication: Research - peer-review › Journal article – Annual report year: 2011
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TY - JOUR
T1 - Implementation of multivariate linear mixed-effects models in the analysis of indoor climate performance experiments
A1 - Jensen,Kasper Lynge
A1 - Spliid,Henrik
A1 - Toftum,Jørn
AU - Jensen,Kasper Lynge
AU - Spliid,Henrik
AU - Toftum,Jørn
PB - Springer
PY - 2011
Y1 - 2011
N2 - The aim of the current study was to apply multivariate mixed-effects modeling to analyze experimental data on the relation between air quality and the performance of office work. The method estimates in one step the effect of the exposure on a multi-dimensional response variable, and yields important information on the correlation between the different dimensions of the response variable, which in this study was composed of both subjective perceptions and a two-dimensional performance task outcome. Such correlation is typically not included in the output from univariate analysis methods. Data originated from three different series of experiments investigating the effects of air quality on performance. The example analyses resulted in a significant and positive correlation between two performance tasks, indicating that the two tasks to some extent measured the same dimension of mental performance. The analysis seems superior to conventional univariate statistics and the information provided may be important for the design of performance experiments in general and for the conclusions that can be based on such studies.
AB - The aim of the current study was to apply multivariate mixed-effects modeling to analyze experimental data on the relation between air quality and the performance of office work. The method estimates in one step the effect of the exposure on a multi-dimensional response variable, and yields important information on the correlation between the different dimensions of the response variable, which in this study was composed of both subjective perceptions and a two-dimensional performance task outcome. Such correlation is typically not included in the output from univariate analysis methods. Data originated from three different series of experiments investigating the effects of air quality on performance. The example analyses resulted in a significant and positive correlation between two performance tasks, indicating that the two tasks to some extent measured the same dimension of mental performance. The analysis seems superior to conventional univariate statistics and the information provided may be important for the design of performance experiments in general and for the conclusions that can be based on such studies.
KW - Indoor air quality
KW - Multivariate mixed-effects modeling
KW - Statistical analysis
KW - Experimental design
KW - Performance
UR - http://www.springerlink.com/content/gv867252q84527x3/
U2 - 10.1007/s00484-011-0404-y
DO - 10.1007/s00484-011-0404-y
JO - International Journal of Biometeorology
JF - International Journal of Biometeorology
SN - 0020-7128
IS - 1
VL - 56
SP - 129
EP - 136
ER -