‏388.00 ₪


‏388.00 ₪
יצא לאור ב
עמודים / Pages
תאריך יציאה לאור
1 ביולי 2013
שם סדרה
Chapman & Hall/CRC Biostatistics Series
Statistical Analysis of Human Growth and Development is an accessible and practical guide to a wide range of basic and advanced statistical methods that are useful for studying human growth and development. Designed for nonstatisticians and statisticians new to the analysis of growth and development data, the book collects methods scattered throughout the literature and explains how to use them to solve common research problems. It also discusses how well a method addresses a specific scientific question and how to interpret and present the analytic results. Stata is used to implement the analyses, with Stata codes and macros for generating example data sets, a detrended Q-Q plot, and weighted maximum likelihood estimation of binary items available on the book's CRC Press web page. After reviewing research designs and basic statistical tools, the author discusses the use of existing tools to transform raw data into analyzable variables and back-transform them to raw data. He covers regression analysis of quantitative, binary, and censored data as well as the analysis of repeated measurements and clustered data. He also describes the development of new growth references and developmental indices, the generation of key variables based on longitudinal data, and the processes to verify the validity and reliability of measurement tools. Looking at the larger picture of research practice, the book concludes with coverage of missing values, multiplicity problems, and multivariable regression. Along with two simulated data sets, numerous examples from real experimental and observational studies illustrate the concepts and methods. Although the book focuses on examples of anthropometric measurements and changes in cognitive, social-emotional, locomotor, and other abilities, the ideas are applicable to many other physical and psychosocial phenomena, such as lung function and depressive symptoms.
מידע נוסף
מהדורה 1
עמודים / Pages 378
פורמט Hardback
ISBN10 143987154X
יצא לאור ב London
תאריך יציאה לאור 1 ביולי 2013
תוכן עניינים Introduction Overview Human Growth Human Development Statistical Considerations Causal Reasoning and Study Designs Causality Study Designs Basic Statistical Concepts and Tools Normal Distribution Statistical Inference and Significance Standardized Scores Statistical Programming Quantifying Growth and Development: Use of Existing Tools Growth Development Change Scores Regression Analysis of Quantitative Outcomes Least-Squares Regression Quantile Regression Covariate-Adjusted Variables Regression Analysis of Binary Outcomes Basic Concepts Introduction to Generalized Linear Models Logistic Regression Log-Binomial and Binomial Regression Models Regression Analysis of Censored Outcomes Fundamentals Regression Analysis of Right-Censored Data Analysis of Interval-Censored Data Analysis of Repeated Measurements and Clustered Data Introduction Robust Variance Estimator Analysis of Subject-Level Summary Statistics Mixed Models Quantifying Growth: Development of New Tools Capturing Nonlinear Relationships Modeling Quantifying Development: Development of New Tools Summary Index Based on Binary Items Summary Index Based on Quantitative Variables Defining Growth and Development: Longitudinal Measurements Expected Change and Unexplained Residuals Reference Intervals for Longitudinal Monitoring Conditional Scores by Quantile Regression Trajectory Characteristics Validity and Reliability Concepts Statistical Methods Further Topics Missing Values and Imputation Introduction When Is Missing Data (Not) a Problem? Interpolation and Extrapolation Mixed Models Multiple Imputation Imputing Censored Data Multiple Comparisons The Problem When Not to Do Multiplicity Adjustment Strategies of Analysis to Prevent Multiplicity P-Value Adjustments Close Testing Procedure Regression Analysis Strategy Introduction Rationale of Using Multivariable Regression Point Measures, Change Scores, and Unexplained Residuals Issues in Variable Selection Interaction Role of Prior Knowledge References Appendix A: Stata Codes to Generate Simulated Clinical Trial (SCT) Dataset Appendix B: Stata Codes to Generate Simulated Longitudinal Study (SLS) Dataset Appendix C: Stata Program for Detrended Q-Q Plot Appendix D: Weighted Maximum Likelihood Estimation for Binary Items Index