Milestone Moments in Getting your PhDin Qualitative Research is a guide for research students completing higher degrees with a focus on the importance of language and terminology of the theoretical and practical requirements of a given research program. The book responds to a lack of preparedness among many entrants into higher-degrees in contemporary higher education. The need among non-traditional entrants into higher-degrees for a strong background in core academic principles is made pressing due to the lack of preparation many students undergo prior to enrolment. This book might be consulted by research students as they proceed through the various milestones that may form part of a higher-degree.
Multilevel Analysis of Educational Data focuses on the principles and procedures used in the evaluation of educational progress. The selection first offers information on some applications of multilevel models to educational data, empirical Bayes methods, and a hierarchical item-response model for educational testing. Discussions focus on the interface between levels, group-level model for content elements, an application of empirical Bayes, validity generalization, improving law school validity studies, and summarizing evidence in randomized experiments on coaching. The text then takes a look at difficulties with Bayesian inference for random effects and multilevel aspects of varying parameters in structural models. The book elaborates on models for multilevel response variables with an application to growth curves and the issues and problems emerging from the application of multilevel models in British studies of school effectiveness, including enduring questions, two-level models, estimation and prediction, and econometric random coefficient modeling. The selection is a dependable reference for educators and researchers interested in the evaluation of educational progress.
Analysis of Qualitative Data, Volume 2: New Developments focuses on the variety of models used in the analysis of qualitative data. The book first elaborates on multinomial response models and incomplete tables. Discussions focus on models for incomplete tables with ordered categories, incomplete two-way tables and migration, multinomial response models for one or more continuous independent variables, and multinomial response models for two-way tables. The book also reviews symmetrical tables and adjustment of data, including the adjustment of marginal totals using unsaturated models, symmetry models for multi-way tables, and distance models. The publication ponders on latent-class models, as well as models with several latent variables, iterative proportional fitting and latent-class models, maximum likelihood equations for the traditional latent-class model, and the scoring algorithm. The manuscript is a vital reference for researchers interested in the models used in the analysis of qualitative data.
Research Methods in Human Skeletal Biology serves as the one location readers can go to not only learn how to conduct research in general, but how research is specifically conducted within human skeletal biology. It outlines the current types of research being conducted within each sub-specialty of skeletal biology, and gives the reader the tools to set up a research project in skeletal biology. It also suggests several ideas for potential projects. Each chapter has an inclusive bibliography, which can serve as a good jumpstart for project references.
This book examines the following factors: sponsorship of research, control of the dissemination of research, effects of dominant research paradigms, financial interests of authors, publishers, and editors, role of new technologies (for example, Web 2.0).It is widely accepted among researchers and educators that the peer review process, the reputation of the publisher and examination of the author's credentials are the gold standards for assessing the quality of research and information. However, the traditional gold standards are not sufficient, and the effective evaluation of information requires the consideration of additional factors. Controversies about positive evaluations of new medications that appear in peer-reviewed journals, the financial reports on Enron prior to the revelations that led to its collapse, and obstacles to the publication of research that does not conform to dominant paradigms are just a few examples that indicate the need for a more sophisticated and nuanced approach to evaluating information.Each of the factors is discussed in a factual manner, supported by many examples that illustrate not only the nature of the issues but also their complexity. Practical suggestions for the evaluation of information are an integral part of the text.
Longitudinal research is a broad field in which substantial advances have been made over the past decade. Unlike many of the existing books that only address the analysis of information. The Handbook of Longitudinal Research covers design and measurement as well as the data analysis. Designed for use by a wide-ranging audience, this Handbook not only includes perspective on the methodological and data analysis problems in longitudinal research but it also includes contributors' data sets that enable readers who lack sophisticated statistics skills to move from theories about longitudinal data into practice. As the comprehensive reference, this Handbook has no direct competition as most books in this subject area are more narrowly specialized and are pitched at a high mathematical level.
The Rosetta Stone of Science is a useful and practical guide to presenting scientific research in the English language. It is written specifically for scientists who would like to improve the effectiveness with which they use the English language and improve their communicative skills in order to become published and develop more confidence in presenting their work at international conferences.Part 1 of the book covers the style preferred by today's leading journals, discusses how to prepare models for writing research papers, and provides advice for writing abstracts, proposals, and editing. Examples of cover letters are also given. Part 2 discusses the various arts and techniques used by successful presenters at scientific conferences. The content of the book is presented in a light, simple and informative manner making The Rosetta Stone of Science an entertaining and instructive read. This book will prove invaluable to all scientists, research fellows, post-docs, and graduate students whose first language is not English.
Statistical Design-Chemometrics is applicable to researchers and professionals who wish to perform experiments in chemometrics and carry out analysis of the data in the most efficient way possible. The language is clear, direct and oriented towards real applications. The book provides 106 exercises with answers to accompany the study of theoretical principles. Forty two cases studies with real data are presented showing designs and the complete statistical analyses for problems in the areas chromatography, electroanalytical and electrochemistry, calibration, polymers, gas adsorption, semiconductors, food technology, biotechnology, photochemistry, catalysis, detergents and ceramics. These studies serve as a guide that the reader can use to perform correct data analyses.
An Introduction to Wavelets and Other Filtering Methods in Finance and Economics presents a unified view of filtering techniques with a special focus on wavelet analysis in finance and economics. It emphasizes the methods and explanations of the theory that underlies them. It also concentrates on exactly what wavelet analysis (and filtering methods in general) can reveal about a time series. It offers testing issues which can be performed with wavelets in conjunction with the multi-resolution analysis. The descriptive focus of the book avoids proofs and provides easy access to a wide spectrum of parametric and nonparametric filtering methods. Examples and empirical applications will show readers the capabilities, advantages, and disadvantages of each method.
Multivariate statistics and mathematical models provide flexible and powerful tools essential in most disciplines. Nevertheless, many practicing researchers lack an adequate knowledge of these techniques, or did once know the techniques, but have not been able to keep abreast of new developments. The Handbook of Applied Multivariate Statistics and Mathematical Modeling explains the appropriate uses of multivariate procedures and mathematical modeling techniques, and prescribe practices that enable applied researchers to use these procedures effectively without needing to concern themselves with the mathematical basis. The Handbook emphasizes using models and statistics as tools. The objective of the book is to inform readers about which tool to use to accomplish which task. Each chapter begins with a discussion of what kinds of questions a particular technique can and cannot answer. As multivariate statistics and modeling techniques are useful across disciplines, these examples include issues of concern in biological and social sciences as well as the humanities.