Analysis Of Questionnaire Data With R
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Analysis of Questionnaire Data with R
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.
Analysis of Questionnaire Data with R
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.
Complex Surveys
A complete guide to carrying out complex survey analysis using R As survey analysis continues to serve as a core component of sociological research, researchers are increasingly relying upon data gathered from complex surveys to carry out traditional analyses. Complex Surveys is a practical guide to the analysis of this kind of data using R, the freely available and downloadable statistical programming language. As creator of the specific survey package for R, the author provides the ultimate presentation of how to successfully use the software for analyzing data from complex surveys while also utilizing the most current data from health and social sciences studies to demonstrate the application of survey research methods in these fields. The book begins with coverage of basic tools and topics within survey analysis such as simple and stratified sampling, cluster sampling, linear regression, and categorical data regression. Subsequent chapters delve into more technical aspects of complex survey analysis, including post-stratification, two-phase sampling, missing data, and causal inference. Throughout the book, an emphasis is placed on graphics, regression modeling, and two-phase designs. In addition, the author supplies a unique discussion of epidemiological two-phase designs as well as probability-weighting for causal inference. All of the book's examples and figures are generated using R, and a related Web site provides the R code that allows readers to reproduce the presented content. Each chapter concludes with exercises that vary in level of complexity, and detailed appendices outline additional mathematical and computational descriptions to assist readers with comparing results from various software systems. Complex Surveys is an excellent book for courses on sampling and complex surveys at the upper-undergraduate and graduate levels. It is also a practical reference guide for applied statisticians and practitioners in the social and health sciences who use statistics in their everyday work.