Practical Research with Children is designed to help the reader understand techniques for research with children, based on real world experience. The book describes a wide range of research methods, focusing equally on quantitative and qualitative approaches, and considers how different methods can be integrated. It highlights the benefits and challenges of each method and gives emphasis to best practice, with expert guidance on how to avoid potential pitfalls in order to obtain valuable insights into how children develop. The volume includes fifteen chapters arranged over three sections. Each chapter explores a particular method, or combination of methods, and discusses both theoretical and practical issues, using a diversity of domains, including different ages, cultures, populations and settings. Uniquely, the book includes newer methods (such as eye tracking and digital technologies) alongside well-established behavioural methods which are used for research with children. With contributions from internationally renowned researchers and practitioners from a range of disciplines, the book will be indispensable reading for a wide audience, including for students in psychology, education and nursing undertaking research projects with children, and also for anyone looking to understand the research behind current theories in child development.

This text focuses on the experimental methods and the associated terminology encountered in the research literature of psychology. Initially, the content is kept simple, so as not to distract from the information on research technique and philosophy. Interesting psychological questions from well researched areas are then examined in detail, permitting a fuller discussion of the problems encountered in specific paradigms. It is in this fashion that the book offers both methods and content. Unique features of this text include: * a detailed discussion of the process of theorizing, coupled with a close examination of psychological constructs, offers the reader an opportunity to see how psychologists think about, develop, and modify their theories, and the part played by research in changing explanations of behavior. * Although it is common for psychologists to be self-conscious in their reasoning, it is uncommon to see an analysis of the logic that they use to draw conclusions. Presenting material that is rarely verbalized but readily acknowledged by experienced researchers, the text contains an overt analysis of the logic of drawing conclusions from research. * Instructors are given a choice among 15 chapters to focus on or combine to suit the course's concentration. For example, instructors have the option of focusing on experimental psychology or a broad-based course including material on research methods in experimental, social, clinical, and applied psychology. * Courses in experimental psychology or research methods are required for every psychology major. Statistical understanding is vital for this curriculum, and this text contains a comprehensive chapter on statistics making it ideal for courses that combine statistics and experimental methods. Other important coverage includes: * an all-inclusive summary of the material found in an introductory statistics class. Although courses in research methods and experimental psychology usually have a statistics prerequisite, the students rarely remember the material when entering the research course. This text provides the instructor with the option of simply assigning the statistics information as a review, rather than repeating the lectures. If the course requirements are such as to necessitate a joint statistics and research methods course -- with the instructor lecturing on both topics -- this text could serve as the single text for the course. A helpful discussion -- accompanied by a valuable table -- demonstrates how to choose an appropriate statistic. All necessary formulas and other familiar statistical procedures -- illustrating computational steps -- are also featured. * a detailed discussion of how to develop tests for use in research. Aside from the value of this information for any researcher, it can be particularly helpful to students who are required to develop original experiments. * an elaborate discussion of methodological issues in outcome research, using smoking cessation and weight reduction programs as examples. Test bank disks for Experimental Methods in Psychology, -- free to adopters -- consist of an average of six short-answer, 11 fill-in-the-blank, and 11 multiple-choice questions for each chapter. The files are in both ASCII and Word-for-Windows formats.

Offering a deep look into the moral uncertainty in the contemporary social sciences and American society, this book explores an in-depth solution. This solution, as articulated by Pitirim A. Sorokin in the 20th century, is the theory of Integralism; a perspective dating back to Plato, Aristotle and Aquinas. Sorokin initially applied Integralism by locating and analyzing three dominant super socio-cultural systems over 2500 years of Graeco-Roman and Western history. Each super system was unified by a central philosophical principle based either on materialism (the senses), or the rational, or the supersensory/super-rational. A super system declines when it reaches the limits of its potential to achieve its true reality and value, to be replaced by another super system. Sorokin described a trendless rotation of the three super socio-cultural systems. The current dominant super socio-cultural system in the West is a materialist version emphasizing science and technology with little thought given to supersensory/super-rational reality. Sorokin asserted contemporary materialist culture was in a state of collapse due to the breakup of its moral values. As a consequence he saw a struggle for power occurring between egoistic individuals and groups often resulting in revolutions, wars and inter-human strife. In response to the one sided materialist view of reality the goal of Integralism is to unify all three forms of reality into an integral culture that harmoniously balances materialist and supersensory/super-rational orientations. A solution to the contemporary moral confusion, Sorokin argued, can be found in the application of supra-conscious intuition that would enable a human to know what is eternal in the ordinary and reach the transcendent; an experience not accessible to the senses or the rational intellect alone. The supra-conscious is the source for reaching the supreme moral value; creative unselfish altruism which can be shared by all cultures to produce peace and harmony in the world.

The EBBS Publications Series is designed to provide researchers and students with authoritative, topical reviews of major areas in the brain and behaviour sciences. Each volume includes specially commissioned and edited chapters by leading researchers, presented in a lively and accessible style ideal for the non-specialist. The study of appetite is of major interest to psychologists and neuroscientists, and is understood to involve components relating to both disciplines. Psychological research looks at the cues which guide appetitive behaviour, and the cognitive mechanisms used to interpret cues and influence choice of action. Neuroscience research looks at the neural substrates for these behavioural processes. This is the first volume to bring the two perspectives together covering the areas of eating, drinking, sexual behaviour, drug addiction, and gambling. It will be of interest to behavioural researchers in general, and to clinicians interested in abnormal forms of appetite.

This volume contains a collection of essays and discussions which serve as an introduction and guide to current research in the area of drawing inferences from self-selected samples. This topic is of direct interest to a professional audience of survey researchers, pollsters, market researchers, policymakers, statisticians, demographers, economists, and sociologists. The essays themselves and their associated critical discussions are clear and careful; the contributors are among the foremost experts in the field.

The Trouble with Twin Studies questions popular genetic explanations of human behavioral differences based upon the existing body of twin research. Psychologist Jay Joseph outlines the fallacies of twin studies in the context of the ongoing decades-long failure to discover genes for human behavioral differences, including IQ, personality, and the major psychiatric disorders. This volume critically examines twin research, with a special emphasis on reared-apart twin studies, and incorporates new and updated perspectives, analyses, arguments, and evidence.

How can we account for the sudden appearance of such dazzling artists and scientists as Mozart, Shakespeare, Darwin, or Einstein? How can we define such genius? What conditions or personality traits seem to produce exceptionally creative people? Is the association between genius and madness really just a myth? These and many other questions are brilliantly illuminated in The Origins of Genius. Dean Simonton convincingly argues that creativity can best be understood as a Darwinian process of variation and selection. The artist or scientist generates a wealth of ideas, and then subjects these ideas to aesthetic or scientific judgment, selecting only those that have the best chance to survive and reproduce. Indeed, the true test of genius is the ability to bequeath an impressive and influential body of work to future generations. Simonton draws on the latest research into creativity and explores such topics as the personality type of the genius, whether genius is genetic or produced by environment and education, the links between genius and mental illness (Darwin himself was emotionally and mentally unwell), the high incidence of childhood trauma, especially loss of a parent, amongst Nobel Prize winners, the importance of unconscious incubation in creative problem-solving, and much more. Simonton substantiates his theory by examining and quoting from the work of such eminent figures as Henri Poincare, W. H. Auden, Albert Einstein, Marie Curie, Charles Darwin, Niels Bohr, and many others. For anyone intrigued by the spectacular feats of the human mind, The Origins of Genius offers a revolutionary new way of understanding the very nature of creativity.

Presenting the proceedings of a conference held at Syracuse University in honor of S.S. Stevens, a pioneer in the scaling of sensory magnitudes and the originator of the method of magnitude estimation, this volume brings together the work of 20 authorities on the procedures of ratio scaling. These experts--psychophysicists, physiologists, and theoreticians--offer their views on whether or not psychological magnitudes can be measured and whether the judgments of psychological magnitudes constitute the basis for the construction of a ratio scale. Also discussed is the question of whether any single method could stand out as a potential standard technique for measuring psychological magnitudes.

Without question, statistics is one of the most challenging courses for students in the social and behavioral sciences. Enrolling in their first statistics course, students are often apprehensive or extremely anxious toward the subject matter. And while IBM SPSS is one of the more easy-to-use statistical software programs available, for anxious students who realize they not only have to learn statistics but also new software, the task can seem insurmountable. Keenly aware of students' anxiety with statistics (and the fact that this anxiety can affect performance), Ronald D. Yockey has written SPSS Demystified: A Simple Guide and Reference, now in its fourth edition. Through a comprehensive, step-by-step approach, this text is consistently and specifically designed to both alleviate anxiety toward the subject matter and build a successful experience analyzing data in SPSS. Topics covered in the text are appropriate for most introductory and intermediate statistics and research methods courses. Key features of the text: Step-by-step instruction and screenshots Designed to be hands-on with the user performing the analyses alongside on their computer as they read through each chapter Call-out boxes provided, highlighting important information as appropriate SPSS output explained, with written results provided using the popular, widely recognized APA format End-of-chapter exercises included, allowing for additional practice SPSS datasets available on the publisher's website New to the Fourth Edition: Fully updated to SPSS 28 Updated screenshots in full color to reflect changes in SPSS software system (version 28) Exercises updated with up-to-date examples Exact p-values provided (consist with APA recommendations)

Prepares readers to analyze data and interpret statistical results using the increasingly popular R more quickly than other texts through LessR extensions which remove the need to program. By introducing R through less R, readers learn how to organize data for analysis, read the data into R, and produce output without performing numerous functions and programming first. Readers can select the necessary procedure and change the relevant variables without programming. Quick Starts introduce readers to the concepts and commands reviewed in the chapters. Margin notes define, illustrate, and cross-reference the key concepts. When readers encounter a term previously discussed, the margin notes identify the page number to the initial introduction. Scenarios highlight the use of a specific analysis followed by the corresponding R/lessR input and an interpretation of the resulting output. Numerous examples of output from psychology, business, education, and other social sciences demonstrate how to interpret results and worked problems help readers test their understanding. www.lessRstats.com website features the lessR program, the book's 2 data sets referenced in standard text and SPSS formats so readers can practice using R/lessR by working through the text examples and worked problems, PDF slides for each chapter, solutions to the book's worked problems, links to R/lessR videos to help readers better understand the program, and more. New to this edition: o upgraded functionality and data visualizations of the lessR package, which is now aesthetically equal to the ggplot 2 R standard o new features to replace and extend previous content, such as aggregating data with pivot tables with a simple lessR function call.

This edited volume provides both conceptual and practical information for conducting and evaluating evidence-based outcome studies. It encompasses psychotherapy research for traditional mental health disorders (eg. depression, anxiety), as well as psychosocial-based treatments provided to medical patient populations to have impact either on the disease process itself (pain, cardiovascular risk) or to improve the quality of life of such individuals. This is a hands-on book, whose major emphasis is on the practical nuts-and-bolts implementation of psychosocial-based RCTs from conception to completion.

Signal detection theory--as developed in electrical engineering and based on statistical decision theory--was first applied to human sensory discrimination 40 years ago. The theoretical intent was to provide a valid model of the discrimination process; the methodological intent was to provide reliable measures of discrimination acuity in specific sensory tasks. An analytic method of detection theory, called the relative operating characteristic (ROC), can isolate the effect of the placement of the decision criterion, which may be variable and idiosyncratic, so that a pure measure of intrinsic discrimination acuity is obtained. For the past 20 years, ROC analysis has also been used to measure the discrimination acuity or inherent accuracy of a broad range of practical diagnostic systems. It was widely adopted by methodologists in the field of information retrieval, is increasingly used in weather forecasting, and is the generally preferred method in clinical medicine, primarily in radiology. This book attends to both themes, ROC analysis in the psychology laboratory and in practical diagnostic settings, and to their essential unity. The focus of this book is on detection and recognition as fundamental tasks that underlie most complex behaviors. As defined here, they serve to distinguish between two alternative, confusable stimulus categories, which may be perceptual or cognitive categories in the psychology laboratory, or different states of the world in practical diagnostic tasks. This book on signal detection theory in psychology was written by one of the developers of the theory, who co-authored with D.M. Green the classic work published in this area in 1966 (reprinted in 1974 and 1988). This volume reviews the history of the theory in engineering, statistics, and psychology, leading to the separate measurement of the two independent factors in all discrimination tasks, discrimination acuity and decision criterion. It extends the previous book to show how in several areas of psychology--in vigilance and memory--what had been thought to be discrimination effects were, in reality, effects of a changing criterion. The book shows that data plotted in terms of the relative operating characteristic have essentially the same form across the wide range of discrimination tasks in psychology. It develops the implications of this ROC form for measures of discrimination acuity, pointing up the valid ones and identifying several common, but invalid, ones. The area under the binormal ROC is seen to be supported by the data; the popular measures d' and percent correct are not. An appendix describes the best, current programs for fitting ROCs and estimating their parameters, indices, and standard errors. The application of ROC analysis to diagnostic tasks is also described. Diagnostic accuracy in a wide range of tasks can be expressed in terms of the ROC area index. Choosing the appropriate decision criterion for a given diagnostic setting--rather than considering some single criterion to be natural and fixed--has a major impact on the efficacy of a diagnostic process or system. Illustrated here by separate chapters are diagnostic systems in radiology, information retrieval, aptitude testing, survey research, and environments in which imminent dangerous conditions must be detected. Data from weather forecasting, blood testing, and polygraph lie detection are also reported. One of these chapters describes a general approach to enhancing the accuracy of diagnostic systems.

The crux of the debate between proponents of behavioral psychology and cognitive psychology focuses on the issue of accessibility. Cognitivists believe that mental mechanisms and processes are accessible, and that their inner workings can be inferred from experimental observations of behavior. Behaviorists, on the contrary, believe that mental processes and mechanisms are inaccessible, and that nothing important about them can be inferred from even the most cleverly designed empirical studies. One argument that is repeatedly raised by cognitivists is that even though mental processes are not directly accessible, this should not be a barrier to unravelling the nature of the inner mental processes and mechanisms. Inference works for other sciences, such as physics, so why not psychology? If physics can work so successfully with their kind of inaccessibility to make enormous theoretical progress, then why not psychology? As with most previous psychological debates, there is no "killer argument" that can provide an unambiguous resolution. In its absence, author William Uttal explores the differing properties of physical and psychological time, space, and mathematics before coming to the conclusion that there are major discrepancies between the properties of the respective subject matters that make the analogy of comparable inaccessibilities a false one.

See How Graphics Reveal Information Graphical Data Analysis with R shows you what information you can gain from graphical displays. The book focuses on why you draw graphics to display data and which graphics to draw (and uses R to do so). All the datasets are available in R or one of its packages and the R code is available at rosuda.org/GDA. Graphical data analysis is useful for data cleaning, exploring data structure, detecting outliers and unusual groups, identifying trends and clusters, spotting local patterns, evaluating modelling output, and presenting results. This book guides you in choosing graphics and understanding what information you can glean from them. It can be used as a primary text in a graphical data analysis course or as a supplement in a statistics course. Colour graphics are used throughout.

Drawing on the authors' extensive research in the analysis of categorical longitudinal data, Latent Markov Models for Longitudinal Data focuses on the formulation of latent Markov models and the practical use of these models. Numerous examples illustrate how latent Markov models are used in economics, education, sociology, and other fields. The R and MATLAB (R) routines used for the examples are available on the authors' website. The book provides you with the essential background on latent variable models, particularly the latent class model. It discusses how the Markov chain model and the latent class model represent a useful paradigm for latent Markov models. The authors illustrate the assumptions of the basic version of the latent Markov model and introduce maximum likelihood estimation through the Expectation-Maximization algorithm. They also cover constrained versions of the basic latent Markov model, describe the inclusion of the individual covariates, and address the random effects and multilevel extensions of the model. After covering advanced topics, the book concludes with a discussion on Bayesian inference as an alternative to maximum likelihood inference. As longitudinal data become increasingly relevant in many fields, researchers must rely on specific statistical and econometric models tailored to their application. A complete overview of latent Markov models, this book demonstrates how to use the models in three types of analysis: transition analysis with measurement errors, analyses that consider unobserved heterogeneity, and finding clusters of units and studying the transition between the clusters.

Analysis of Variance, Design, and Regression: Linear Modeling for Unbalanced Data, Second Edition presents linear structures for modeling data with an emphasis on how to incorporate specific ideas (hypotheses) about the structure of the data into a linear model for the data. The book carefully analyzes small data sets by using tools that are easily scaled to big data. The tools also apply to small relevant data sets that are extracted from big data. New to the Second Edition Reorganized to focus on unbalanced data Reworked balanced analyses using methods for unbalanced data Introductions to nonparametric and lasso regression Introductions to general additive and generalized additive models Examination of homologous factors Unbalanced split plot analyses Extensions to generalized linear models R, Minitab (R), and SAS code on the author's website The text can be used in a variety of courses, including a yearlong graduate course on regression and ANOVA or a data analysis course for upper-division statistics students and graduate students from other fields. It places a strong emphasis on interpreting the range of computer output encountered when dealing with unbalanced data.

This engaging book helps readers identify and then discard 52 misconceptions about data and statistical summaries. The focus is on major concepts contained in typical undergraduate and graduate courses in statistics, research methods, or quantitative analysis. Interactive Internet exercises that further promote undoing the misconceptions are found on the book's website. The author's accessible discussion of each misconception has five parts: The Misconception - a brief description of the misunderstanding Evidence that the Misconception Exists - examples and claimed prevalence Why the Misconception is Dangerous - consequence of having the misunderstanding Undoing the Misconception - how to think correctly about the concept Internet Assignment - an interactive activity to help readers gain a firm grasp of the statistical concept and overcome the misconception. The book's statistical misconceptions are grouped into 12 chapters that match the topics typically taught in introductory/intermediate courses. However, each of the 52 discussions is self-contained, thus allowing the misconceptions to be covered in any order without confusing the reader. Organized and presented in this manner, the book is an ideal supplement for any standard textbook. An ideal supplement for undergraduate and graduate courses in statistics, research methods, or quantitative analysis taught in psychology, education, business, nursing, medicine, and the social sciences. The book also appeals to independent researchers interested in undoing their statistical misconceptions.

Originally published in 1987, this book presents papers from the First Conference of European Clinical Psychologists, held at the University of Kent Canterbury in July of that year. It shows some of the most exciting and recent developments in research and innovations in professional practice from many European countries with an overall theme of the WHO strategy of 'Health for all by the year 2000.' The whole range of clinical psychology is covered, including: cognitive therapy, clinical psychology and WHO strategy, the mental health of ethnic minority groups, health psychology, care in the community, and many other topics. The book is likely to be of interest for anyone concerned with the recent history and policies in clinical psychology.

Devising tests that evaluate a nation's educational standing and implement efficacious educational reforms requires a careful balance among the contributions of technology, psychometrics, test design, and the learning sciences. Unlike other forms of adaptive testing, multistage testing (MST) is highly suitable for testing educational achievement because it can be adapted to educational surveys and student testing. Computerized Multistage Testing: Theory and Applications covers the methodologies, underlying technology, and implementation aspects of this type of test design. The book discusses current scientific perspectives and practical considerations for each step involved in setting up an MST program. It covers the history of MST, test design and implementation for various purposes, item pool development and maintenance, IRT-based and classical test theory-based methodologies for test assembly, routing and scoring, equating, test security, and existing software. It also explores current research, existing operational programs, and innovative future assessments using MST. Intended for psychologists, social scientists, and educational measurement scientists, this volume provides the first unified source of information on the design, psychometrics, implementation, and operational use of MST. It shows how to apply theoretical statistical tools to testing in novel and useful ways. It also explains how to explicitly tie the assumptions made by each model to observable (or at least inferable) data conditions. Winner of the 2016 AERA Award for Significant Contribution to Educational Measurement and Research Methodology The 2016 American Education Research Association (AERA) Div. D award committee for Significant Contributions to Educational Measurement and Research Methodology has recognized unanimously this collaborative work advancing the theory and applications of computerized MST. This annual award recognizes published research judged to represent a significant conceptual advancement in the theory and practice of educational measurement and/or educational research methodology. The 2016 award was made under the heading: Measurement, Psychometrics, and Assessment. This collective work, published in 2014 as an edited volume titled Computerized Multistage Testing: Theory and Applications, was cited by the committee both for the originality of the conceptual foundations presented in support of multistage testing and for arguing persuasively for its potential impact on the practice of educational measurement.

Generalized Linear Models for Categorical and Continuous Limited Dependent Variables is designed for graduate students and researchers in the behavioral, social, health, and medical sciences. It incorporates examples of truncated counts, censored continuous variables, and doubly bounded continuous variables, such as percentages. The book provides broad, but unified, coverage, and the authors integrate the concepts and ideas shared across models and types of data, especially regarding conceptual links between discrete and continuous limited dependent variables. The authors argue that these dependent variables are, if anything, more common throughout the human sciences than the kind that suit linear regression. They cover special cases or extensions of models, estimation methods, model diagnostics, and, of course, software. They also discuss bounded continuous variables, boundary-inflated models, and methods for modeling heteroscedasticity. Wherever possible, the authors have illustrated concepts, models, and techniques with real or realistic datasets and demonstrations in R and Stata, and each chapter includes several exercises at the end. The illustrations and exercises help readers build conceptual understanding and fluency in using these techniques. At several points the authors bring together material that has been previously scattered across the literature in journal articles, software package documentation files, and blogs. These features help students learn to choose the appropriate models for their purpose.

Age-Period-Cohort Analysis: New Models, Methods, and Empirical Applications is based on a decade of the authors' collaborative work in age-period-cohort (APC) analysis. Within a single, consistent HAPC-GLMM statistical modeling framework, the authors synthesize APC models and methods for three research designs: age-by-time period tables of population rates or proportions, repeated cross-section sample surveys, and accelerated longitudinal panel studies. The authors show how the empirical application of the models to various problems leads to many fascinating findings on how outcome variables develop along the age, period, and cohort dimensions. The book makes two essential contributions to quantitative studies of time-related change. Through the introduction of the GLMM framework, it shows how innovative estimation methods and new model specifications can be used to tackle the "model identification problem" that has hampered the development and empirical application of APC analysis. The book also addresses the major criticism against APC analysis by explaining the use of new models within the GLMM framework to uncover mechanisms underlying age patterns and temporal trends. Encompassing both methodological expositions and empirical studies, this book explores the ways in which statistical models, methods, and research designs can be used to open new possibilities for APC analysis. It compares new and existing models and methods and provides useful guidelines on how to conduct APC analysis. For empirical illustrations, the text incorporates examples from a variety of disciplines, such as sociology, demography, and epidemiology. Along with details on empirical analyses, software and programs to estimate the models are available on the book's web page.

Test fairness is a moral imperative for both the makers and the users of tests. This book focuses on methods for detecting test items that function differently for different groups of examinees and on using this information to improve tests. Of interest to all testing and measurement specialists, it examines modern techniques used routinely to insure test fairness. Three of these relevant to the book's contents are: * detailed reviews of test items by subject matter experts and members of the major subgroups in society (gender, ethnic, and linguistic) that will be represented in the examinee population * comparisons of the predictive validity of the test done separately for each one of the major subgroups of examinees * extensive statistical analyses of the relative performance of major subgroups of examinees on individual test items.

The Psychology Research Companion: From student project to working life not only gives you the skills and confidence to conduct your psychology research project at university, but is the first book to show how these skills will help you get ahead in your first job in the workplace. Jessica S. Horst, an American psychologist teaching in the UK, takes you through every step of the research process; from conceiving your research question and choosing a research methodology, to organizing your time and resources effectively. The book includes sections on ethics, data management, working with research participants and report writing, but each chapter is also informed by the wider aim of providing a toolkit for working life. Each chapter is packed with tips and skills that can be taken into the workplace, including working collaboratively and organising your workload, as well as discussing your research project in interview situations and when applying for jobs. This invaluable guide will appeal to all undergraduate and postgraduate psychology students whose aim is to learn a set of transferable research skills as well as to obtain a good degree result.

This text introduces teachers to research methods they can use to examine their own classrooms in order to become more effective teachers. Becoming familiar with classroom-based research methods not only enables teachers to do research in their own classrooms, it also provides a basis for assessing the findings of existing research. McKay emphasizes throughout that what a teacher chooses to examine will dictate which method is most effective. Each chapter includes activities to help readers apply the methods described in the chapter, often by analyzing research data. *Chapter I, Classroom Research, introduces the reader to major research purposes and research types as they relate to classroom research, the distinction between quantitative and qualitative research, the formulation of research questions and research designs, and ethical issues in research. *Chapter II, Researching Teachers and Learners, presents research methods that can be used to examine teachers' and learners' attitudes and behaviors: action research, survey research, interviews, verbal reports, diary studies, case studies, and ethnographies. *Chapter III, Researching Classroom Discourse, deals with methods that can be used to study the oral and written discourse of classrooms: interaction analysis, discourse analysis, text analysis, and ways to examine the social and political assumptions underlying the choice and presentation of content in second language teaching materials. *Chapter IV, Writing Research Reports, provides guidelines for both thesis writing and journal articles. Researching Second Language Classrooms is an ideal text for TESOL research methods courses and an essential resource for inservice teachers who wish to undertake classroom research.

In this collection, international contributors come together to discuss how qualitative and quantitative methods can be used in psychotherapy research. The book considers the advantages and disadvantages of each approach, and recognises how each method can enhance our understanding of psychotherapy. Divided into two parts, the book begins with an examination of quantitative research and discusses how we can transfer observations into numbers and statistical findings. Chapters on quantitative methods cover the development of new findings and the improvement of existing findings, identifying and analysing change, and using meta-analysis. The second half of the book comprises chapters considering how qualitative and mixed methods can be used in psychotherapy research. Chapters on qualitative and mixed methods identify various ways to strengthen the trustworthiness of qualitative findings via rigorous data collection and analysis techniques. Adapted from a special issue of Psychotherapy Research, this volume will be key reading for researchers, academics, and professionals who want a greater understanding of how a particular area of research methods can be used in psychotherapy.