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Using Multivariate Statistics

[신간의 별자리x] 우리/미술, 그리고 ‘슬픔의 박물관’

The detection of psychiatric illness by questionnaire

The complete title of this book runs ‘Analyzing Linguistic Data: A Practical Introduction to Statistics using R’ and as such it very well reflects the purpose and spirit of the book. The author guides the reader in about 350 pages from descriptive and basic statistical methods over classification and clustering to (generalised) linear and mixed models. Each of the methods is introduced in the context of concrete linguistic problems and demonstrated on exciting datasets from current research in the language sciences. In line with its practical orientation, the book focuses primarily on using the methods and interpreting the results. This implies that the mathematical treatment of the techniques is held at a minimum if not absent from the book. In return, the reader is provided with very detailed explanations on how to conduct the analyses using R [1]. The first chapter sets the tone being a 20-page introduction to R. For this and all subsequent chapters, the R code is intertwined with the chapter text and the datasets and functions used are conveniently packaged in the languageR package that is available on the Comprehensive R Archive Network (CRAN). With this approach, the author has done an excellent job in enabling researchers and students alike to reproduce the analyses and learn by doing. Another quality as a textbook is the fact that every chapter ends with Workbook sections where the user is invited to exercise his or her analysis skills on supplemental datasets. Full solutions including code, results and comments are given in Appendix A (30 pages). Instructors are therefore very well served by this text, although they might want to balance the book with some more mathematical treatment depending on the target audience. After the introductory chapter on R, the book opens on graphical data exploration. Chapter 3 treats probability distributions and common sampling distributions. Under basic statistical methods (Chapter 4), distribution tests and tests on means and variances are covered. Chapter 5 deals with clustering and classification. Strangely enough, the clustering section has material on PCA, factor analysis, correspondence analysis and includes only one subsection on clustering, devoted notably to hierarchical partitioning methods. The classification part deals with decision trees, discriminant analysis and support vector machines. The regression chapter (Chapter 6) treats linear models, generalised linear models, piecewise linear models and a substantial section on models for lexical richness. The final chapter on mixed models is particularly interesting as it is one of the few text book accounts that introduce the reader to using the (innovative) lme4 package of Douglas Bates which implements linear mixed-effects models. Moreover, the case studies included in this

Analyzing linguistic data: a practical introduction to statistics using R

Research has shown that, even though the conditions seem to comply with current standards for indoor environmental quality (IEQ) based on single-dose response relationships, staying indoors is not good for our health. In the last three decades, many studies all over the world have been performed to identify and solve health and comfort problems of occupants. In our current standards, IEQ is still described with quantitative dose-related indicators, expressed in number and/or ranges of numbers for each of the factors (indoor air, lighting, acoustics and thermal aspects). Individual differences in needs and preferences of occupants (over time) are not accounted for. Other stressors and factors, whether of psychological, physiological, personal, social or environmental nature, are rarely considered. Interactions of stressors and effects at and between human and environment level are ignored. The focus is on preventing negative effects: positive effects are usually not considered. There is a need for an integrated analysis approach for assessing indoor environmental quality, which takes account of the combined effects of positive and negative stress factors in buildings on people (patterns), interactions, as well as the (dynamic) preferences and needs of occupants (profiles) and dynamics of the environment.

https://iopscience.iop.org/article/10.1088/1757-899X/609/2/022001/pdf

The need for understanding the indoor environmental factors and its effects on occupants through an integrated analysis

To find out whether a surface finishing was preferred under different lighting conditions by school children, in the light test chamber of the SenseLab, 335 children from previous studied schools were asked to assess a desk surface during different light conditions. A two-way randomized design was used to test children’s assessments for six school desks table tops (brown, yellow and grey wood, and, normal, matt and reflective white), under three different light conditions: energizing, calming, and focusing. A statistically relevant relationship was found for the three wooden surfaces, but none for the white ones. Such results may be due to the fact that better contrast between the participants’ form and the surface appeared with the wooden-like surfaces, as opposed to that with the white surfaces. Similarly, white surfaces’ characteristics seemed to be more difficult to assess (mattness, reflectiveness, opacity) as opposed to those for the wooden-like surfaces (colour yellow, brown, grey).

/pdf/table-top-surface-appraisal-by-school-children-under-1cmaq2d1jc.pdf

Table top surface appraisal by school children under different lighting conditions tested in the Senselab

The HOPE European research project aimed to look at a possible relationship between the energy performance of a building and the well-being (health and comfort) of their occupants. An interdisciplinary survey resulted in guidelines to increase the number of energy-efficient buildings that are at the same time healthy and comfortable. These guidelines are presented, together with experimental evidence for their reliability.

Design of healthy, comfortable, and energy-efficient buildings

Building-related health symptoms are multifactorial, hence a comprehensive study is needed to identify associations of such symptoms with building aspects. Previous studies have identified certain building characteristics as risk factors for both dry eyes and headaches, which are among the most prevalent symptoms suffered by office workers. This study investigated associations of dry eyes and headaches with building characteristics in outpatient areas because these conditions may vary between office and hospital buildings. A survey was performed in six hospital buildings, which included administering a questionnaire to 556 outpatient workers and an inspection of the building locations, services and 127 outpatient rooms. Multivariate regression models were produced for dry eyes and headaches. Both models were adjusted for personal and work-related aspects. The prevalence of self-reported dry eyes and headaches in outpatient areas was related to building-related aspects that affect the indoor air quality and visual quality, and to room types. In general, this study is consistent with previous office studies. However, a specific finding of this study is the association of the most frequently used room types and the presence of a window to the corridor with dry eyes and headaches.

/pdf/building-characteristics-associated-with-self-reported-dry-4rcvhv9fzi.pdf

Building characteristics associated with self-reported dry eyes and headaches of outpatient workers in hospital buildings:

For the establishment of basic requirements and needs a different view on indoor environment quality (IEQ) is required. An integrated approach towards risk assessment of IEQ, in which the focus is on real exposure situations rather than only on single components, will form the basis for creating healthy and comfortable indoor environments. Additional, a multidisciplinary interactive top-down approach is required to facilitate the design, construction, maintenance and operation of an indoor environment, in which the architect as well as the other stakeholders fulfil a new or different role. It is important to accept that IEQ is a multi-level, multi-factor and multi-stakeholders issue, therefore cooperation is a must.

/pdf/understanding-the-indoor-environment-how-to-assess-and-3t76lud3as.pdf

Philomena M. Bluyssen

Papers

The need for understanding the indoor environmental factors and its effects on occupants through an integrated analysis

Table top surface appraisal by school children under different lighting conditions tested in the Senselab

Design of healthy, comfortable, and energy-efficient buildings

Building characteristics associated with self-reported dry eyes and headaches of outpatient workers in hospital buildings:

Understanding the Indoor Environment: How To Assess and Improve Indoor Environmental Quality of People?