Analysis of Questionnaire Data with R

Zusatztext "? useful for readers wishing to transfer knowledge of survey analysis and its application in other statistical packages to R. Insights in how a practitioner can use R to analyze one particular survey are very helpful and can be readily applied to one's own work. ? this text would be handy to have on my bookshelf to refer to when conducting survey analyses. ? a good book to have ?"-Gregory E. Gilbert! The American Statistician! November 2014"? excellently written and documented. The text covers many of the real-life concerns that arise when analyzing questionnaire data ? . I recommend the book to any researchers and post-graduates embarking upon questionnaire design and analysis for the first time! especially in the field of social sciences."-International Statistical Review! 80! 2012"[T]he book is nicely compact! well organized! and for the reader who is already familiar with R! sampling! and survey methodology! it is quite easy to jump from section to section and read through them quickly. ? I have found myself already referring to portions of the text as I consider various survey analyses! and I have recommended at least portions of it to students and colleagues. ? an interesting and well-written book ? ."-Ronald D. Fricker! Jr.! Journal of Statistical Software! Vol. 46! January 2012 Informationen zum Autor After studying mathematics and getting his Ph.D. in biostatistics, the author graduated as a child and adolescent psychiatrist. He is now professor in biostatistics in Paris-Sud University, head of a master in public health and of the research lab "public health and mental health". Klappentext Addressing the problem of analysis of questionnaire data and interpretation of results, this book proposes a methodology that uses R software. The author takes a practical approach to the subject, presenting principles first followed by detailed examples of their application to real data. He discusses principles of data management and manipulation, and covers descriptive statistics, statistical modeling, reliability, and missing data. The book focuses on R packages that are readily available and integrates discussion of their implementation and code throughout. All the data sets and R code packages are provided on a website. Zusammenfassung While theoretical statistics relies primarily on mathematics and hypothetical situations, statistical practice is a translation of a question formulated by a researcher into a series of variables linked by a statistical tool. As with written material, there are almost always differences between the meaning of the original text and translated text. Additionally, many versions can be suggested, each with their advantages and disadvantages. Analysis of Questionnaire Data with R translates certain classic research questions into statistical formulations. As indicated in the title, the syntax of these statistical formulations is based on the well-known R language, chosen for its popularity, simplicity, and power of its structure. Although syntax is vital, understanding the semantics is the real challenge of any good translation. In this book, the semantics of theoretical-to-practical translation emerges progressively from examples and experience, and occasionally from mathematical considerations. Sometimes the interpretation of a result is not clear, and there is no statistical tool really suited to the question at hand. Sometimes data sets contain errors, inconsistencies between answers, or missing data. More often, available statistical tools are not formally appropriate for the given situation, making it difficult to assess to what extent this slight inadequacy affects the interpretation of results. Analysis of Questionnaire Data with R tackles these and other common challenges in the practice of statistics. Inhaltsverzeichnis Introduction. Description of R...

Autorentext
After studying mathematics and getting his Ph.D. in biostatistics, the author graduated as a child and adolescent psychiatrist. He is now professor in biostatistics in Paris-Sud University, head of a master in public health and of the research lab "public health and mental health".

Klappentext
Addressing the problem of analysis of questionnaire data and interpretation of results, this book proposes a methodology that uses R software. The author takes a practical approach to the subject, presenting principles first followed by detailed examples of their application to real data. He discusses principles of data management and manipulation, and covers descriptive statistics, statistical modeling, reliability, and missing data. The book focuses on R packages that are readily available and integrates discussion of their implementation and code throughout. All the data sets and R code packages are provided on a website.

Zusammenfassung
While theoretical statistics relies primarily on mathematics and hypothetical situations, statistical practice is a translation of a question formulated by a researcher into a series of variables linked by a statistical tool. As with written material, there are almost always differences between the meaning of the original text and translated text. Additionally, many versions can be suggested, each with their advantages and disadvantages.Analysis of Questionnaire Data with R translates certain classic research questions into statistical formulations. As indicated in the title, the syntax of these statistical formulations is based on the well-known R language, chosen for its popularity, simplicity, and power of its structure. Although syntax is vital, understanding the semantics is the real challenge of any good translation. In this book, the semantics of theoretical-to-practical translation emerges progressively from examples and experience, and occasionally from mathematical considerations. Sometimes the interpretation of a result is not clear, and there is no statistical tool really suited to the question at hand. Sometimes data sets contain errors, inconsistencies between answers, or missing data. More often, available statistical tools are not formally appropriate for the given situation, making it difficult to assess to what extent this slight inadequacy affects the interpretation of results. Analysis of Questionnaire Data with R tackles these and other common challenges in the practice of statistics.

Inhalt
Introduction. Description of Responses. Description of Relationships between Variables. Confidence Intervals and Statistical Tests of Hypothesis. Introduction to Linear, Logistic, Poisson, and Other Regression Models. About Statistical Modelling. Principles for the Validation of a Composite Score. 8 Introduction to Structural Equation Modelling. Introduction to Data Manipulation using R. Appendix A: The Analysis of Questionnaire Data using R: Memory Card. References. Index.

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