图书简介
This book consists of four parts with 32 chapters adapted for four short courses, from the basic to the advanced levels of medical statistics (biostatistics), ideal for biomedical students . Part 1 is a compulsory course of Basic Statistics with descriptive statistics, parameter estimation and hypothesis test, simple correlation and regression. Part 2 is a selective course on Study Design and Implementation with sampling survey, interventional study, observational study, diagnosis study, data sorting and article writing. Part 3 is a specially curated course of Multivariate Analyses with complex analyses of variance, variety of regressions and classical multivariate analyses. Part 4 is a seminar course on Introduction to Advanced Statistical Methods with meta-analysis, time series, item response theory, structure equation model, multi-level model, bio-informatics, genetic statistics and data mining.
The main body of each chapter is followed by five practical sections: Report Writing, Case Discrimination, Computer Experiments, Frequently Asked Questions and Summary, and Practice & Think. Moreover, there are 2 attached Appendices, Appendix A includes Introductions to SPSS, Excel and R respectively, and Appendix B includes all the programs, data and printouts for Computer Experiments in addition to the Tests for Review and the reference answers for Case Discrimination as well as Practice & Think.
This book can be used as a textbook for biomedical students at both under- and postgraduate levels. It can also serve as an importantguide for researchers, professionals and officers in the biomedical field.
Introduction; Basic Concepts and Methods: Statistical Description; Probability Distribution; Parameter Estimation; Hypothesis Testing; Comparison of Means Between 2 Groups; Comparison of Means Among Multiple Groups; Comparison of Distributions of Categorical Variables; Analysis for Association; Simple Linear Regression; Design and Implementation of Bio-Medical Research: Sampling Survey; Interventional Study; Clinical Trial; Observational Comparative Effectiveness Research; Diagnostic Test; Sample Size Estimation; Missing Data; Statistical Guidelines for Medical Papers; Frequently Used Powerful Statistical Methods: Analysis of Variance for Complicated Designs; Multiple Linear Regression; Logistic Regression; Survival Analysis; Discriminant Analysis and Classification Tree; Cluster Analysis; Principal Component Analysis and Factor Analysis; Selected Topics of Advanced Statistics: Meta Analysis; Time Series; Structural Equation Model; Multi-Level Model; Item Response Theory; Statistics for Genetics; Statistics for Bio-Informatics; Data Mining; Appendices: Introduction for Statistical Software; Supplement for the Text; Statistical Tables; Index;
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