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Biomathematics. Biometry. Biostatistics --- Epidemiology --- Human genetics --- medische statistiek --- medische genetica --- biomathematica --- biostatistiek --- genetica --- epidemiologie --- biometrie

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Multivariate analysis --- Longitudinal method --- Cluster analysis --- Data processing.

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This book covers the statistical models and methods that are used to understand human genetics, following the historical and recent developments of human genetics. Starting with Mendel’s first experiments to genome-wide association studies, the book describes how genetic information can be incorporated into statistical models to discover disease genes. All commonly used approaches in statistical genetics (e.g. aggregation analysis, segregation, linkage analysis, etc), are used, but the focus of the book is modern approaches to association analysis. Numerous examples illustrate key points throughout the text, both of Mendelian and complex genetic disorders. The intended audience is statisticians, biostatisticians, epidemiologists and quantitatively- oriented geneticists and health scientists wanting to learn about statistical methods for genetic analysis, whether to better analyze genetic data, or to pursue research in methodology. A background in intermediate level statistical methods is required. The authors include few mathematical derivations, and the exercises provide problems for students with a broad range of skill levels. No background in genetics is assumed. Dr. Laird is a Professor of Biostatistics in the Biostatistics Department at the Harvard School of Public Health. Dr. Laird has contributed to methodology in many different fields, including missing data, EM-algorithm, meta-analysis, statistical genetics, and has coauthored a book with Garrett Fitzmaurice and James Ware on Applied Longitudinal Analysis. She is the recipient of many awards and prizes, including Fellow of the American Statistical Association, the American Association for the Advancement of Science, the Florence Nightingale Award, and the Janet Norwood Award. Dr. Lange is an Associate Professor in the Biostatistics Department at the Harvard School of Public Health. After his PhD in Statistics at the University of Reading (UK), he has worked extensively in the field of statistical genetics. Dr. Lange has been the director of the Institute of Genome Mathematics at the University of Bonn and has received several awards in mathematics and genetics. Dr. Lange is the developer of the PBAT package.

Genetics --- Biometry. --- Biological statistics --- Biology --- Biometrics (Biology) --- Biostatistics --- Statistical methods. --- Statistical methods --- Statistics. --- Human genetics. --- Epidemiology. --- Biometrics (Biology). --- Biostatistics. --- Statistics for Life Sciences, Medicine, Health Sciences. --- Human Genetics. --- Biometrics. --- Biomathematics --- Statistics --- Diseases --- Public health --- Heredity, Human --- Human biology --- Physical anthropology --- Statistical analysis --- Statistical data --- Statistical science --- Mathematics --- Econometrics --- Human genetics --- Statistics .

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This book covers the statistical models and methods that are used to understand human genetics, following the historical and recent developments of human genetics. Starting with Mendel's first experiments to genome-wide association studies, the book describes how genetic information can be incorporated into statistical models to discover disease genes. All commonly used approaches in statistical genetics (e.g. aggregation analysis, segregation, linkage analysis, etc), are used, but the focus of the book is modern approaches to association analysis. Numerous examples illustrate key points throughout the text, both of Mendelian and complex genetic disorders. The intended audience is statisticians, biostatisticians, epidemiologists and quantitatively- oriented geneticists and health scientists wanting to learn about statistical methods for genetic analysis, whether to better analyze genetic data, or to pursue research in methodology. A background in intermediate level statistical methods is required. The authors include few mathematical derivations, and the exercises provide problems for students with a broad range of skill levels. No background in genetics is assumed. Dr. Laird is a Professor of Biostatistics in the Biostatistics Department at the Harvard School of Public Health. Dr. Laird has contributed to methodology in many different fields, including missing data, EM-algorithm, meta-analysis, statistical genetics, and has coauthored a book with Garrett Fitzmaurice and James Ware on Applied Longitudinal Analysis. She is the recipient of many awards and prizes, including Fellow of the American Statistical Association, the American Association for the Advancement of Science, the Florence Nightingale Award, and the Janet Norwood Award. Dr. Lange is an Associate Professor in the Biostatistics Department at the Harvard School of Public Health. After his PhD in Statistics at the University of Reading (UK), he has worked extensively in the field of statistical genetics. Dr. Lange has been the director of the Institute of Genome Mathematics at the University of Bonn and has received several awards in mathematics and genetics. Dr. Lange is the developer of the PBAT package.

Biomathematics. Biometry. Biostatistics --- Epidemiology --- Human genetics --- medische statistiek --- medische genetica --- biomathematica --- biostatistiek --- genetica --- epidemiologie --- biometrie

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"Since the publication of the first edition, the authors have solicited feedback from both the instructors who use the book as a text for their courses as well as the researchers who use the book as a resource for their research. Thus, the improved Second Edition of Applied Longitudinal Analysis features many additions and revisions based on the feedback of readers, making it the go-to reference for applied use in public health, epidemiology, and pharmaceutical sciences"

303.4 --- AA / International- internationaal --- Statistische verdeling (wiskundige statistiek). Asymptotic theory. Density functions. --- Longitudinal Studies --- Multivariate Analysis --- Biometry --- Longitudinal method. --- Longitudinal studies. --- Medical statistics. --- Multivariate Analysis. --- Multivariate analysis. --- Regression Analysis. --- Regression analysis. --- Methods. --- Longitudinal method --- Regression Analysis --- Multivariate analysis --- Medical statistics --- methods --- Regression analysis --- Analysis, Regression --- Linear regression --- Regression modeling --- Structural equation modeling --- Multivariate distributions --- Multivariate statistical analysis --- Statistical analysis, Multivariate --- Analysis of variance --- Mathematical statistics --- Matrices --- Health --- Health statistics --- Medicine --- Statistics --- Longitudinal research --- Longitudinal studies --- Methodology --- Research --- Social sciences --- Statistische verdeling (wiskundige statistiek). Asymptotic theory. Density functions --- Statistical methods --- Mathematical analysis --- analyse (wiskunde) --- Biometry - methods