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Growth Curves
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Download or read book Growth Curves written by Anant Kshirsagar and published by CRC Press. This book was released on 1995-04-19 with total page 392 pages. Available in PDF, EPUB and Kindle. Book excerpt: This work describes several statistical techniques for studying repeated measures data, presenting growth curve methods applicable to biomedical, social, animal, agricultural and business research. It details the multivariate development of growth science and repeated measures experiments, covering time-moving covariates, exchangable errors, bioassay results, missing data procedures and nonparametric and Bayesian methods.
Book Synopsis Growth Curve Analysis and Visualization Using R by : Daniel Mirman
Download or read book Growth Curve Analysis and Visualization Using R written by Daniel Mirman and published by CRC Press. This book was released on 2017-09-07 with total page 192 pages. Available in PDF, EPUB and Kindle. Book excerpt: Learn How to Use Growth Curve Analysis with Your Time Course Data An increasingly prominent statistical tool in the behavioral sciences, multilevel regression offers a statistical framework for analyzing longitudinal or time course data. It also provides a way to quantify and analyze individual differences, such as developmental and neuropsychological, in the context of a model of the overall group effects. To harness the practical aspects of this useful tool, behavioral science researchers need a concise, accessible resource that explains how to implement these analysis methods. Growth Curve Analysis and Visualization Using R provides a practical, easy-to-understand guide to carrying out multilevel regression/growth curve analysis (GCA) of time course or longitudinal data in the behavioral sciences, particularly cognitive science, cognitive neuroscience, and psychology. With a minimum of statistical theory and technical jargon, the author focuses on the concrete issue of applying GCA to behavioral science data and individual differences. The book begins with discussing problems encountered when analyzing time course data, how to visualize time course data using the ggplot2 package, and how to format data for GCA and plotting. It then presents a conceptual overview of GCA and the core analysis syntax using the lme4 package and demonstrates how to plot model fits. The book describes how to deal with change over time that is not linear, how to structure random effects, how GCA and regression use categorical predictors, and how to conduct multiple simultaneous comparisons among different levels of a factor. It also compares the advantages and disadvantages of approaches to implementing logistic and quasi-logistic GCA and discusses how to use GCA to analyze individual differences as both fixed and random effects. The final chapter presents the code for all of the key examples along with samples demonstrating how to report GCA results. Throughout the book, R code illustrates how to implement the analyses and generate the graphs. Each chapter ends with exercises to test your understanding. The example datasets, code for solutions to the exercises, and supplemental code and examples are available on the author’s website.
Book Synopsis Higher-Order Growth Curves and Mixture Modeling with Mplus by : Kandauda A.S. Wickrama
Download or read book Higher-Order Growth Curves and Mixture Modeling with Mplus written by Kandauda A.S. Wickrama and published by Routledge. This book was released on 2021-11-24 with total page 346 pages. Available in PDF, EPUB and Kindle. Book excerpt: This practical introduction to second-order and growth mixture models using Mplus introduces simple and complex techniques through incremental steps. The authors extend latent growth curves to second-order growth curve and mixture models and then combine the two using normal and non-normal (e.g., categorical) data. To maximize understanding, each model is presented with basic structural equations, figures with associated syntax that highlight what the statistics mean, Mplus applications, and an interpretation of results. Examples from a variety of disciplines demonstrate the use of the models and exercises allow readers to test their understanding of the techniques. A comprehensive introduction to confirmatory factor analysis, latent growth curve modeling, and growth mixture modeling is provided so the book can be used by readers of various skill levels. The book’s datasets are available on the web. New to this edition: * Two new chapters providing a stepwise introduction and practical guide to the application of second-order growth curves and mixture models with categorical outcomes using the Mplus program. Complete with exercises, answer keys, and downloadable data files. * Updated illustrative examples using Mplus 8.0 include conceptual figures, Mplus program syntax, and an interpretation of results to show readers how to carry out the analyses with actual data. This text is ideal for use in graduate courses or workshops on advanced structural equation, multilevel, longitudinal or latent variable modeling, latent growth curve and mixture modeling, factor analysis, multivariate statistics, or advanced quantitative techniques (methods) across the social and behavioral sciences.
Book Synopsis Higher-Order Growth Curves and Mixture Modeling with Mplus by : Kandauda A.S. Wickrama
Download or read book Higher-Order Growth Curves and Mixture Modeling with Mplus written by Kandauda A.S. Wickrama and published by Routledge. This book was released on 2016-04-14 with total page 345 pages. Available in PDF, EPUB and Kindle. Book excerpt: This practical introduction to second-order and growth mixture models using Mplus introduces simple and complex techniques through incremental steps. The authors extend latent growth curves to second-order growth curve and mixture models and then combine the two. To maximize understanding, each model is presented with basic structural equations, figures with associated syntax that highlight what the statistics mean, Mplus applications, and an interpretation of results. Examples from a variety of disciplines demonstrate the use of the models and exercises allow readers to test their understanding of the techniques. A comprehensive introduction to confirmatory factor analysis, latent growth curve modeling, and growth mixture modeling is provided so the book can be used by readers of various skill levels. The book’s datasets are available on the web. Highlights include: -Illustrative examples using Mplus 7.4 include conceptual figures, Mplus program syntax, and an interpretation of results to show readers how to carry out the analyses with actual data. -Exercises with an answer key allow readers to practice the skills they learn. -Applications to a variety of disciplines appeal to those in the behavioral, social, political, educational, occupational, business, and health sciences. -Data files for all the illustrative examples and exercises at www.routledge.com/9781138925151 allow readers to test their understanding of the concepts. -Point to Remember boxes aid in reader comprehension or provide in-depth discussions of key statistical or theoretical concepts. Part 1 introduces basic structural equation modeling (SEM) as well as first- and second-order growth curve modeling. The book opens with the basic concepts from SEM, possible extensions of conventional growth curve models, and the data and measures used throughout the book. The subsequent chapters in part 1 explain the extensions. Chapter 2 introduces conventional modeling of multidimensional panel data, including confirmatory factor analysis (CFA) and growth curve modeling, and its limitations. The logical and theoretical extension of a CFA to a second-order growth curve, known as curve-of-factors model (CFM), are explained in Chapter 3. Chapter 4 illustrates the estimation and interpretation of unconditional and conditional CFMs. Chapter 5 presents the logical and theoretical extension of a parallel process model to a second-order growth curve, known as factor-of-curves model (FCM). Chapter 6 illustrates the estimation and interpretation of unconditional and conditional FCMs. Part 2 reviews growth mixture modeling including unconditional growth mixture modeling (Ch. 7) and conditional growth mixture models (Ch. 8). How to extend second-order growth curves (curve-of-factors and factor-of-curves models) to growth mixture models is highlighted in Chapter 9. Ideal as a supplement for use in graduate courses on (advanced) structural equation, multilevel, longitudinal, or latent variable modeling, latent growth curve and mixture modeling, factor analysis, multivariate statistics, or advanced quantitative techniques (methods) taught in psychology, human development and family studies, business, education, health, and social sciences, this book’s practical approach also appeals to researchers. Prerequisites include a basic knowledge of intermediate statistics and structural equation modeling.
Book Synopsis Contributions to linear discriminant analysis with applications to growth curves by : Edward Kanuti Ngailo
Download or read book Contributions to linear discriminant analysis with applications to growth curves written by Edward Kanuti Ngailo and published by Linköping University Electronic Press. This book was released on 2020-05-06 with total page 47 pages. Available in PDF, EPUB and Kindle. Book excerpt: This thesis concerns contributions to linear discriminant analysis with applications to growth curves. Firstly, we present the linear discriminant function coefficients in a stochastic representation using random variables from the standard univariate distributions. We apply the characterized distribution in the classification function to approximate the classification error rate. The results are then extended to large dimension asymptotics under assumption that the dimension p of the parameter space increases together with the sample size n to infinity such that the ratio converges to a positive constant c (0, 1). Secondly, the thesis treats repeated measures data which correspond to multiple measurements that are taken on the same subject at different time points. We develop a linear classification function to classify an individual into one out of two populations on the basis of the repeated measures data that when the means follow a growth curve structure. The growth curve structure we first consider assumes that all treatments (groups) follows the same growth profile. However, this is not necessarily true in general and the problem is extended to linear classification where the means follow an extended growth curve structure, i.e., the treatments under the experimental design follow different growth profiles. At last, a function of the inverse Wishart matrix and a normal distribution finds its application in portfolio theory where the vector of optimal portfolio weights is proportional to the product of the inverse sample covariance matrix and a sample mean vector. Analytical expressions for higher order moments and non-central moments of the portfolio weights are derived when the returns are assumed to be independently multivariate normally distributed. Moreover, the expressions for the mean, variance, skewness and kurtosis of specific estimated weights are obtained. The results are complemented using a Monte Carlo simulation study, where data from the multivariate normal and t-distributions are discussed. Den här avhandlingen studerar diskriminantanalys, klassificering av tillväxtkurvor och portföljteori. Diskriminantanalys och klassificering är flerdimensionella tekniker som används för att separera olika mängder av objekt och för att tilldela nya objekt till redan definierade grupper (så kallade klasser). En klassisk metod är att använda Fishers linjära diskriminantfunktion och när alla parametrar är kända så kan man enkelt beräkna sannolikheterna för felklassificering. Tyvärr är så sällan fallet, utan parametrarna måste skattas från data, och då blir Fishers linjära diskriminantfunktion en funktion av en Wishartmatris och multivariat normalfördelade vektorer. I den här avhandlingen studerar vi hur man kan approximativt beräkna sannolikheten för felklassificering under antagande att dimensionen på parameterrummet ökar tillsammans med antalet observationer genom att använda en särskild stokastisk representation av diskriminantfunktionen. Upprepade mätningar över tiden på samma individ eller objekt går att modellera med så kallade tillväxtkurvor. Vid klassificering av tillväxtkurvor, eller rättare sagt av upprepade mätningar för en ny individ, bör man ta tillvara på både den spatiala- och temporala informationen som finns hos dessa observationer. Vi vidareutvecklar Fishers linjära diskriminantfunktion att passa för upprepade mätningar och beräknar asymptotiska sannolikheter för felklassificering. Till sist kan man notera att snarlika funktioner av Wishartmatriser och multivariat normalfördelade vektorer dyker upp när man vill beräkna de optimala vikterna i portföljteori. Genom en stokastisk representation studerar vi egenskaperna hos portföljvikterna och gör dessutom en simuleringsstudie för att förstå vad som händer när antagandet om normalfördelning inte är uppfyllt.
Book Synopsis Site Index and Height Growth Curves for Managed, Even-aged Stands of Douglas-fir East of the Cascades in Oregon and Washington by : P. H. Cochran
Download or read book Site Index and Height Growth Curves for Managed, Even-aged Stands of Douglas-fir East of the Cascades in Oregon and Washington written by P. H. Cochran and published by . This book was released on 1979 with total page 24 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Site Index and Height Growth Curves for Managed, Even-aged Stands of White Or Grand Fir East of the Cascades in Oregon and Washington by : Collin D. Bevins
Download or read book Site Index and Height Growth Curves for Managed, Even-aged Stands of White Or Grand Fir East of the Cascades in Oregon and Washington written by Collin D. Bevins and published by . This book was released on 1978 with total page 438 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Site Index and Height Growth Curves for Managed, Even-aged Stands of White Or Grand Fir East of the Cascades in Oregon and Washington by : P. H. Cochran
Download or read book Site Index and Height Growth Curves for Managed, Even-aged Stands of White Or Grand Fir East of the Cascades in Oregon and Washington written by P. H. Cochran and published by . This book was released on 1979 with total page 20 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis 2000 CDC Growth Charts for the United States by :
Download or read book 2000 CDC Growth Charts for the United States written by and published by . This book was released on 2002 with total page 208 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Latent Growth Curve Modeling by : Kristopher J. Preacher
Download or read book Latent Growth Curve Modeling written by Kristopher J. Preacher and published by SAGE Publications. This book was released on 2008-06-27 with total page 113 pages. Available in PDF, EPUB and Kindle. Book excerpt: Latent growth curve modeling (LGM)—a special case of confirmatory factor analysis designed to model change over time—is an indispensable and increasingly ubiquitous approach for modeling longitudinal data. This volume introduces LGM techniques to researchers, provides easy-to-follow, didactic examples of several common growth modeling approaches, and highlights recent advancements regarding the treatment of missing data, parameter estimation, and model fit. The book covers the basic linear LGM, and builds from there to describe more complex functional forms (e.g., polynomial latent curves), multivariate latent growth curves used to model simultaneous change in multiple variables, the inclusion of time-varying covariates, predictors of aspects of change, cohort-sequential designs, and multiple-group models. The authors also highlight approaches to dealing with missing data, different estimation methods, and incorporate discussion of model evaluation and comparison within the context of LGM. The models demonstrate how they may be applied to longitudinal data derived from the NICHD Study of Early Child Care and Youth Development (SECCYD).. Key Features · Provides easy-to-follow, didactic examples of several common growth modeling approaches · Highlights recent advancements regarding the treatment of missing data, parameter estimation, and model fit · Explains the commonalities and differences between latent growth model and multilevel modeling of repeated measures data · Covers the basic linear latent growth model, and builds from there to describe more complex functional forms such as polynomial latent curves, multivariate latent growth curves, time-varying covariates, predictors of aspects of change, cohort-sequential designs, and multiple-group models
Download or read book Growth Modeling written by Kevin J. Grimm and published by Guilford Publications. This book was released on 2016-10-17 with total page 558 pages. Available in PDF, EPUB and Kindle. Book excerpt: Growth models are among the core methods for analyzing how and when people change. Discussing both structural equation and multilevel modeling approaches, this book leads readers step by step through applying each model to longitudinal data to answer particular research questions. It demonstrates cutting-edge ways to describe linear and nonlinear change patterns, examine within-person and between-person differences in change, study change in latent variables, identify leading and lagging indicators of change, evaluate co-occurring patterns of change across multiple variables, and more. User-friendly features include real data examples, code (for Mplus or NLMIXED in SAS, and OpenMx or nlme in R), discussion of the output, and interpretation of each model's results. User-Friendly Features *Real, worked-through longitudinal data examples serving as illustrations in each chapter. *Script boxes that provide code for fitting the models to example data and facilitate application to the reader's own data. *"Important Considerations" sections offering caveats, warnings, and recommendations for the use of specific models. *Companion website supplying datasets and syntax for the book's examples, along with additional code in SAS/R for linear mixed-effects modeling.
Book Synopsis Latent Growth Curve Modeling by : Kristopher J. Preacher
Download or read book Latent Growth Curve Modeling written by Kristopher J. Preacher and published by SAGE. This book was released on 2008-06-27 with total page 113 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Latent Growth Curve Modeling introduces students to a strategy for modeling change over time. This volume offers a unique chance to study this useful research method with easy-to-follow examples of common growth modeling approaches. It addresses ways to fit a variety of advanced statistical models to repeated-measures data, to model change over time, and to assess individual differences in change." "This graduate-level volume is a resource for individual researchers or courses covering longitudinal data analysis, structural equation modeling, developmental methodology, and multivariate techniques."--BOOK JACKET.
Book Synopsis Growth Curve Models and Statistical Diagnostics by : Jian-Xin Pan
Download or read book Growth Curve Models and Statistical Diagnostics written by Jian-Xin Pan and published by Springer Science & Business Media. This book was released on 2012-11-06 with total page 406 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book systematically introduces the theory of the GCM with particular emphasis on their multivariate statistical diagnostics, which are based mainly on recent developments made by the authors and their collaborators. Provided are complete proofs of theorems as well as practical data sets and MATLAB code.
Book Synopsis Growth Curve Models and Applications by : Ratan Dasgupta
Download or read book Growth Curve Models and Applications written by Ratan Dasgupta and published by Springer. This book was released on 2017-09-27 with total page 259 pages. Available in PDF, EPUB and Kindle. Book excerpt: Growth curve models in longitudinal studies are widely used to model population size, body height, biomass, fungal growth, and other variables in the biological sciences, but these statistical methods for modeling growth curves and analyzing longitudinal data also extend to general statistics, economics, public health, demographics, epidemiology, SQC, sociology, nano-biotechnology, fluid mechanics, and other applied areas. There is no one-size-fits-all approach to growth measurement. The selected papers in this volume build on presentations from the GCM workshop held at the Indian Statistical Institute, Giridih, on March 28-29, 2016. They represent recent trends in GCM research on different subject areas, both theoretical and applied. This book includes tools and possibilities for further work through new techniques and modification of existing ones. The volume includes original studies, theoretical findings and case studies from a wide range of applied work, and these contributions have been externally refereed to the high quality standards of leading journals in the field.
Book Synopsis Manual of Neonatal Care by : John P. Cloherty
Download or read book Manual of Neonatal Care written by John P. Cloherty and published by Lippincott Williams & Wilkins. This book was released on 2008 with total page 792 pages. Available in PDF, EPUB and Kindle. Book excerpt: This Spiral® Manual provides a practical approach to the diagnosis and medical management of newborns. Chapters cover maternal, fetal, and neonatal problems and common neonatal procedures. An outline format provides quick access to a large amount of information, and the outline headings are standardized in this edition. The updated coverage includes new information on fetal assessment, survival of premature infants, and perinatal asphyxia and new guidelines on neonatal jaundice. The popular appendices include effects of maternal drugs on the fetus, maternal medications during lactation, and NICU medication guidelines. A neonatal dosing chart and intubation/sedation guidelines appear on the inside covers.
Book Synopsis Growth Curve and Structural Equation Modeling by : Ratan Dasgupta
Download or read book Growth Curve and Structural Equation Modeling written by Ratan Dasgupta and published by Springer. This book was released on 2015-05-29 with total page 306 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book describes some recent trends in GCM research on different subject areas, both theoretical and applied. This includes tools and possibilities for further work through new techniques and modification of existing ones. A growth curve is an empirical model of the evolution of a quantity over time. Growth curves in longitudinal studies are used in disciplines including biology, statistics, population studies, economics, biological sciences, sociology, nano-biotechnology, and fluid mechanics. The volume includes original studies, theoretical findings and case studies from a wide range of applied work. This volume builds on presentations from a GCM workshop held at the Indian Statistical Institute, Giridih, January 18-19, 2014. This book follows the volume Advances in Growth Curve Models, published by Springer in 2013. The results have meaningful application in health care, prediction of crop yield, child nutrition, poverty measurements, estimation of growth rate, and other research areas.
Book Synopsis Advances in Growth Curve Models by : Ratan Dasgupta
Download or read book Advances in Growth Curve Models written by Ratan Dasgupta and published by Springer Science & Business Media. This book was released on 2013-07-23 with total page 278 pages. Available in PDF, EPUB and Kindle. Book excerpt: Advances in Growth Curve Models: Topics from the Indian Statistical Institute is developed from the Indian Statistical Institute's A National Conference on Growth Curve Models. This conference took place between March 28-30, 2012 in Giridih, Jharkhand, India. Jharkhand is a tribal area. Advances in Growth Curve Models: Topics from the Indian Statistical Institute shares the work of researchers in growth models used in multiple fields. A growth curve is an empirical model of the evolution of a quantity over time. Case studies and theoretical findings, important applications in everything from health care to population projection, form the basis of this volume. Growth curves in longitudinal studies are widely used in many disciplines including: Biology, Population studies, Economics, Biological Sciences, SQC, Sociology, Nano-biotechnology, and Fluid mechanics. Some included reports are research topics that have just been developed, whereas others present advances in existing literature. Both included tools and techniques will assist students and researchers in their future work. Also included is a discussion of future applications of growth curve models.
