The Oxford Handbook of Quantitative Methods, Vol. 2: Statistical Analysis PDF Download
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Author: Todd D. Little
Publisher: Oxford University Press
ISBN: 0199934908
Category : Psychology
Languages : en
Pages : 784
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Book Description
Research today demands the application of sophisticated and powerful research tools. Fulfilling this need, The Oxford Handbook of Quantitative Methods is the complete tool box to deliver the most valid and generalizable answers to todays complex research questions. It is a one-stop source for learning and reviewing current best-practices in quantitative methods as practiced in the social, behavioral, and educational sciences. Comprising two volumes, this handbook covers a wealth of topics related to quantitative research methods. It begins with essential philosophical and ethical issues related to science and quantitative research. It then addresses core measurement topics before delving into the design of studies. Principal issues related to modern estimation and mathematical modeling are also detailed. Topics in the handbook then segway into the realm of statistical inference and modeling with chapters dedicated to classical approaches as well as modern latent variable approaches. Numerous chapters associated with longitudinal data and more specialized techniques round out this broad selection of topics. Comprehensive, authoritative, and user-friendly, this two-volume set will be an indispensable resource for serious researchers across the social, behavioral, and educational sciences.
Author: Todd D. Little
Publisher: Oxford University Press
ISBN: 0199934908
Category : Psychology
Languages : en
Pages : 784
Get Book Here
Book Description
Research today demands the application of sophisticated and powerful research tools. Fulfilling this need, The Oxford Handbook of Quantitative Methods is the complete tool box to deliver the most valid and generalizable answers to todays complex research questions. It is a one-stop source for learning and reviewing current best-practices in quantitative methods as practiced in the social, behavioral, and educational sciences. Comprising two volumes, this handbook covers a wealth of topics related to quantitative research methods. It begins with essential philosophical and ethical issues related to science and quantitative research. It then addresses core measurement topics before delving into the design of studies. Principal issues related to modern estimation and mathematical modeling are also detailed. Topics in the handbook then segway into the realm of statistical inference and modeling with chapters dedicated to classical approaches as well as modern latent variable approaches. Numerous chapters associated with longitudinal data and more specialized techniques round out this broad selection of topics. Comprehensive, authoritative, and user-friendly, this two-volume set will be an indispensable resource for serious researchers across the social, behavioral, and educational sciences.
Author: Janet M. Box-Steffensmeier
Publisher: Cambridge University Press
ISBN: 1316060500
Category : Political Science
Languages : en
Pages : 297
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Book Description
Time series, or longitudinal, data are ubiquitous in the social sciences. Unfortunately, analysts often treat the time series properties of their data as a nuisance rather than a substantively meaningful dynamic process to be modeled and interpreted. Time Series Analysis for the Social Sciences provides accessible, up-to-date instruction and examples of the core methods in time series econometrics. Janet M. Box-Steffensmeier, John R. Freeman, Jon C. Pevehouse and Matthew P. Hitt cover a wide range of topics including ARIMA models, time series regression, unit-root diagnosis, vector autoregressive models, error-correction models, intervention models, fractional integration, ARCH models, structural breaks, and forecasting. This book is aimed at researchers and graduate students who have taken at least one course in multivariate regression. Examples are drawn from several areas of social science, including political behavior, elections, international conflict, criminology, and comparative political economy.
Author: R. A.M. Gregson
Publisher: Psychology Press
ISBN: 1317769333
Category : Psychology
Languages : en
Pages : 462
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Book Description
First published in 1983. Psychological data are segments of life histories; as such they are ordered sequences of observations and by definition time series. Yet they are often anything but well behaved; what regularities and invariances they have are buried from all but the most persistent investigator. The most common methods of representing quantitative results in psychology are frozen outside time; thus they deliberately average out much of the sequential structure that holds any sparse clues to the nature of processes within the organism. This review, whose simple aim is to bring together in an illuminating juxtaposition on basic results in both time series analysis and in experimental psychology, thus. cuts across traditions within psychology.
Author: David McDowall
Publisher:
ISBN: 0190943947
Category : Business & Economics
Languages : en
Pages : 201
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Book Description
Interrupted Time Series Analysis develops a comprehensive set of models and methods for drawing causal inferences from time series. It provides example analyses of social, behavioral, and biomedical time series to illustrate a general strategy for building AutoRegressive Integrated Moving Average (ARIMA) impact models. Additionally, the book supplements the classic Box-Jenkins-Tiao model-building strategy with recent auxiliary tests for transformation, differencing, and model selection. Not only does the text discuss new developments, including the prospects for widespread adoption of Bayesian hypothesis testing and synthetic control group designs, but it makes optimal use of graphical illustrations in its examples. With forty completed example analyses that demonstrate the implications of model properties, Interrupted Time Series Analysis will be a key inter-disciplinary text in classrooms, workshops, and short-courses for researchers familiar with time series data or cross-sectional regression analysis but limited background in the structure of time series processes and experiments.
Author: Patrick T. Brandt
Publisher: SAGE
ISBN: 1412906563
Category : Mathematics
Languages : en
Pages : 121
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Book Description
Many analyses of time series data involve multiple, related variables. Modeling Multiple Time Series presents many specification choices and special challenges. This book reviews the main competing approaches to modeling multiple time series: simultaneous equations, ARIMA, error correction models, and vector autoregression. The text focuses on vector autoregression (VAR) models as a generalization of the other approaches mentioned. Specification, estimation, and inference using these models is discussed. The authors also review arguments for and against using multi-equation time series models. Two complete, worked examples show how VAR models can be employed. An appendix discusses software that can be used for multiple time series models and software code for replicating the examples is available. Key Features: * Offers a detailed comparison of different time series methods and approaches. * Includes a self-contained introduction to vector autoregression modeling. * Situates multiple time series modeling as a natural extension of commonly taught statistical models.
Author: Fred B. Bryant
Publisher: Springer Science & Business Media
ISBN: 148992308X
Category : Psychology
Languages : en
Pages : 320
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Book Description
Many authors have argued that applying social psychology to the solution of real world problems builds better theories. Observers have claimed, for example, that of human behavior applied social psychology reveals more accurate principles because its data are based on people in real-life circumstances (Helmreich, 1975; Saxe & Fine, 1980), provides an opportunity to assess the ecological validity of generalizations derived from laboratory research (Ellsworth, 1977; Leventhal, 1980), and discloses important gaps in existing theories (Fisher, 1982; Mayo & LaFrance, 1980). Undoubtedly, many concrete examples can be mustered in support of these claims. But it also can be argued that applying social psychology to social issues and problems builds better research methods. Special methodological problems arise and new perspectives on old methodological problems emerge when re searchers leave the laboratory and tackle social problems in real-world settings. Along the way, we not only improve existing research techniques but also devel op new research tools, all of which enhance our ability to obtain valid results and thereby to understand and solve socially relevant problems. Indeed, Campbell and Stanley's (1966) seminal work on validity in research design grew out of the application of social science in field settings. In this spirit, the principal aim of this volume is to present examples of methodological advances being made as researchers apply social psychology in real-life settings.
Author: Paul S.P. Cowpertwait
Publisher: Springer Science & Business Media
ISBN: 0387886982
Category : Mathematics
Languages : en
Pages : 262
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Book Description
This book gives you a step-by-step introduction to analysing time series using the open source software R. Each time series model is motivated with practical applications, and is defined in mathematical notation. Once the model has been introduced it is used to generate synthetic data, using R code, and these generated data are then used to estimate its parameters. This sequence enhances understanding of both the time series model and the R function used to fit the model to data. Finally, the model is used to analyse observed data taken from a practical application. By using R, the whole procedure can be reproduced by the reader. All the data sets used in the book are available on the website http://staff.elena.aut.ac.nz/Paul-Cowpertwait/ts/. The book is written for undergraduate students of mathematics, economics, business and finance, geography, engineering and related disciplines, and postgraduate students who may need to analyse time series as part of their taught programme or their research.
Author: Rebecca M. Warner
Publisher: Guilford Press
ISBN: 9781572303386
Category : Social Science
Languages : en
Pages : 244
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Book Description
This book provides a thorough introduction to methods for detecting and describing cyclic patterns in time-series data. It is written both for researchers and students new to the area and for those who have already collected time-series data but wish to learn new ways of understanding and presenting them. Facilitating the interpretation of observations of behavior, physiology, mood, perceptual threshold, social indicator variables, and other responses, the book focuses on practical applications and requires much less mathematical background than most comparable texts. Using real data sets and currently available software (SPSS for Windows), the author employs extensive examples to clarify key concepts. Topics covered include research design issues, preliminary data screening, identification and description of cycles, summary of results across time series, and assessment of relations between time series. Also considered are theoretical questions, problems of interpretation, and potential sources of artifact.
Author: Brent D. Slife
Publisher: SUNY Press
ISBN: 9780791414699
Category : Psychology
Languages : en
Pages : 362
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Book Description
Psychology has been captured by an assumption that is almost totally unrecognized. This assumption--the linearity of time--unduly restricts theory and therapy, yet this restriction is so common, so customary, that it is often completely ignored. This book traces the influence of this assumption and reveals the many overlooked "anomalies" to its dominance. Slife describes the many findings and explanations that are incompatible with linear time in several psychological specialties. He contends that these unnoticed anomalies point to alternative conceptions of time that offer innovative ideas for psychological explanation and treatment.
Author: Mark Pickup
Publisher: SAGE Publications
ISBN: 1483313115
Category : Social Science
Languages : en
Pages : 233
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Book Description
Introducing time series methods and their application in social science research, this practical guide to time series models is the first in the field written for a non-econometrics audience. Giving readers the tools they need to apply models to their own research, Introduction to Time Series Analysis, by Mark Pickup, demonstrates the use of—and the assumptions underlying—common models of time series data including finite distributed lag; autoregressive distributed lag; moving average; differenced data; and GARCH, ARMA, ARIMA, and error correction models. “This volume does an excellent job of introducing modern time series analysis to social scientists who are already familiar with basic statistics and the general linear model.” —William G. Jacoby, Michigan State University
