Statistical Analysis of Human Growth and Development

Yin Bun Cheung is a professor in the Centre for Quantitative Medicine, Office of Clinical Sciences at Duke-NUS Graduate Medical School in Singapore and adjunct professor in the Department of International Health at the University of Tampere in Finland. Dr. Cheung has been studying human growth and development in African and Asian countries for about 15 years.

"… a very useful and well-organised manual to be used by statisticians and non-statisticians. It responds to the problems that may arise on both sides."—Journal of Applied Statistics, 2014"… a very useful overview of the vast array of statistical tools, models and tests, which can be applied to the study of human growth and development and also to some important concepts, which are relevant to epidemiological research more generally. The code provided makes this book particularly accessible to those who are familiar with Stata or who are intending to use this software for their analysis, although the methods described could easily be implemented in other standard statistical software packages."—Corrie Macdonald-Wallis, International Journal of Epidemiology, 2014"The author, Yin Bun Cheung has been part of studies in human growth and development in African and Asian countries for about fifteen years. Thereby, he has recognized the lack of statistical analysis books with an emphasis on this specific field . . . I recommend the book for anyone interested in dealing with data of human growth and development, as it extensively describes how to approach a problem in this field. The book is addressed to researchers and postgraduate students without a broad statistical education. Therefore, basic statistical concepts necessary for following subsequent Book Reviews 1467 chapters are explained at the beginning, and the multitude of examples facilitate understanding and application.—Johanna Straubinger, The International Biometric Society

• Introduction. Causal Reasoning and Study Designs. Basic Statistical Concepts and Tools. Quantifying Growth and Development: Use of Existing Tools. Regression Analysis of Quantitative Outcomes. Regression Analysis of Binary Outcomes. Regression Analysis of Censored Outcomes. Analysis of Repeated Measurements and Clustered Data. Quantifying Growth: Development of New Tools. Quantifying Development: Development of New Tools. Quantifying Growth and Development: Longitudinal Measurements. Validity and Reliability. Missing Values and Imputation. Multiple Comparisons. Regression Analysis Strategy. References. Appendices. Index.