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Experimental design is important enough to merit a book on its own, without statistics, that instead links methodology to a discussion of how psychologists can advance and reject theories about human behaviour. The objective of this book is to fulfil this role. The first four chapters lay the foundations of design in experimental psychology. The first chapter justifies the prominent role given to methodology within the discipline, whilst chapters two and three describe between-subject and within-subject designs. Chapter four compares and contrasts the traditional experimental approach with that of the quasi-experimental, or correlational approach, concluding that the consequences of not recognizing the value of the latter approach can be far-reaching. The following three chapters discuss practical issues involved in running experiments. The first of these offers a comprehensive guide to the student researcher who wants to construct a good questionnaire, including a discussion of reliability and validity issues. The next chapter considers the basic tools of psychological research, whilst both discussing the theoretical problem of how a sample from a population is chosen and offering useful hints on the practical issue of finding adequate populations from which to select participants. The next chapter considers ethical practice within psychological research, written in large part so that psychology students will be better able to anticipate ethical problems in their studies before they occur. The final two chapters consider reporting and reading psychological papers. Chapter eight details what should and should not be included in a laboratory report. The contributors use their collective experience of marking numerous lab reports to highlight common errors and provide solutions. Finally, chapter nine describes the various elements of a journal article, including tips on how to get the best out of your journal reading.

This text is about doing science and the active process of reading, learning, thinking, generating ideas, designing experiments, and the logistics surrounding each step of the research process. In easy-to-read, conversational language, Kim MacLin teaches students experimental design principles and techniques using a tutorial approach in which students read, critique, and analyze over 75 actual experiments from every major area of psychology. She provides them with real-world information about how science in psychology is conducted and how they can participate.Recognizing that students come to an experimental design course with their own interests and perspectives, MacLin covers many subdisciplines of psychology throughout the text, including IO psychology, child psychology, social psychology, behavioral psychology, cognitive psychology, clinical psychology, health psychology, educational/school psychology, legal psychology, and personality psychology, among others. Part I of the text is content oriented and provides an overview of the principles of experimental design. Part II contains annotated research articles for students to read and analyze.New sections on how to critically evaluate media reports of scientific findings (in other words, how to identify ‘fake news'), authorship guidelines and decisions, survey research methods and AI tools have been included. Further, expanded information on the Open Science movement, and on ethics in research, and methods to achieve clarity and precision in thinking and writing are included.This edition is up to date with the latest APA Publication Manual (7th edition) and includes an overview of the bias-free language guidelines, the use of singular'they,'and an ethical compliance checklist.. This text is essential reading for students and researchers interested in and studying experimental design in psychology.

This second edition of Design of Observational Studies is both an introduction to statistical inference in observational studies and a detailed discussion of the principles that guide the design of observational studies. An observational study is an empiric investigation of effects caused by treatments when randomized experimentation is unethical or infeasible. Observational studies are common in most fields that study the effects of treatments on people, including medicine, economics, epidemiology, education, psychology, political science and sociology. The quality and strength of evidence provided by an observational study is determined largely by its design. Design of Observational Studies is organized into five parts. Chapters 2, 3, and 5 of Part I cover concisely many of the ideas discussed in Rosenbaum's Observational Studies (also published by Springer) but in a less technical fashion. Part II discusses the practical aspects of using propensity scores and other tools to create a matched comparison that balances many covariates, and includes an updated chapter on matching in R. In Part III, the concept of design sensitivity is used to appraise the relative ability of competing designs to distinguish treatment effects from biases due to unmeasured covariates. Part IV is new to this edition; it discusses evidence factors and the computerized construction of more than one comparison group. Part V discusses planning the analysis of an observational study, with particular reference to Sir Ronald Fisher's striking advice for observational studies:'make your theories elaborate.'This new edition features updated exploration of causal influence, with four new chapters, a new R package DOS2 designed as a companion for the book, and discussion of several of the latest matching packages for R. In particular, DOS2 allows readers to reproduce many analyses from Design of Observational Studies.

This text is about doing science and the active process of reading, learning, thinking, generating ideas, designing experiments, and the logistics surrounding each step of the research process. In easy-to-read, conversational language, Kim MacLin teaches students experimental design principles and techniques using a tutorial approach in which students read, critique, and analyze over 75 actual experiments from every major area of psychology. She provides them with real-world information about how science in psychology is conducted and how they can participate.Recognizing that students come to an experimental design course with their own interests and perspectives, MacLin covers many subdisciplines of psychology throughout the text, including IO psychology, child psychology, social psychology, behavioral psychology, cognitive psychology, clinical psychology, health psychology, educational/school psychology, legal psychology, and personality psychology, among others. Part I of the text is content oriented and provides an overview of the principles of experimental design. Part II contains annotated research articles for students to read and analyze. Classic articles have been retained and 11 new ones have been added, featuring contemporary case studies, information on the Open Science movement, expanded coverage on ethics in research, and a greater focus on becoming a better writer, clarity and precision in writing, and reducing bias in language.This edition is up to date with the latest APA Publication Manual (7th edition) and includes an overview of the updated bias-free language guidelines, the use of singular'they,'the new ethical compliance checklist, and other key changes in APA style. This text is essential reading for students and researchers interested in and studying experimental design in psychology.

Experiment Design and Statistical Methods introduces the concepts, principles, and techniques for carrying out a practical research project either in real world settings or laboratories - relevant to studies in psychology, education, life sciences, social sciences, medicine, and occupational and management research.The text covers:repeated measures unbalanced and non-randomized experiments and surveys choice of design adjustment for confounding variables model building and partition of variance covariance multiple regressionExperiment Design and Statistical Methods contains a unique extension of the Venn diagram for understanding non-orthogonal design, and it includes exercises for developing the reader's confidence and competence. The book also examines advanced techniques for users of computer packages or data analysis, such as Minitab, SPSS, SAS, SuperANOVA, Statistica, BMPD, SYSTAT, Genstat, and GLIM.

Making Research Relevant is the ideal core textbook for master's-level introduction to research methods courses in mental health. Accessible and user friendly, it is designed to help trainees and practitioners understand, connect, and apply research to clinical practice and day-to-day work with students and clients. The text covers foundational concepts like research ethics and how to best consume research, as well as 11 applied, evaluative, and outcome-based research methods. Easy-to-read chapters are infused with case examples from diverse settings and paired with brief video lectures, which provide vignettes to guide application and visual components that demonstrate how research methods can benefit mental health practitioners in real-world scenarios.

Practice-Based Research shows mental-health practitioners how to establish viable and productive research programs in routine clinical settings. Chapters written by experts in practice-based research use real-world examples to help clinicians work through some of the most common barriers to research output in these settings, including lack of access to institutional review boards, lack of organizational support, and limited access to financial resources. Specialized chapters also provide information on research methods and step-by-step suggestions tailored to a variety of practice settings. This is an essential volume for clinicians interested in establishing successful, long-lasting practice-based research programs.

Designing Experiments and Analyzing Data: A Model Comparison Perspective (3rd edition) offers an integrative conceptual framework for understanding experimental design and data analysis. Maxwell, Delaney, and Kelley first apply fundamental principles to simple experimental designs followed by an application of the same principles to more complicated designs. Their integrative conceptual framework better prepares readers to understand the logic behind a general strategy of data analysis that is appropriate for a wide variety of designs, which allows for the introduction of more complex topics that are generally omitted from other books. Numerous pedagogical features further facilitate understanding: examples of published research demonstrate the applicability of each chapter's content; flowcharts assist in choosing the most appropriate procedure; end-of-chapter lists of important formulas highlight key ideas and assist readers in locating the initial presentation of equations; useful programming code and tips are provided throughout the book and in associated resources available online, and extensive sets of exercises help develop a deeper understanding of the subject. Detailed solutions for some of the exercises and realistic data sets are included on the website (DesigningExperiments.com). The pedagogical approach used throughout the book enables readers to gain an overview of experimental design, from conceptualization of the research question to analysis of the data. The book and its companion website with web apps, tutorials, and detailed code are ideal for students and researchers seeking the optimal way to design their studies and analyze the resulting data.

Designing and conducting experiments involving human participants requires a skillset different from that needed for statistically analyzing the resulting data. The Design and Conduct of Meaningful Experiments Involving Human Participants combines an introduction to scientific culture and ethical mores with specific experimental design and procedural content. Author R. Barker Bausell assumes no statistical background on the part of the reader, resulting in a highly accessible text. Clear instructions are provided on topics ranging from the selection of a societally important outcome variable to potentially efficacious interventions to the conduct of the experiment itself. Early chapters introduce the concept of experimental design in an intuitive manner involving both hypothetical and real-life examples of how people make causal inferences. The fundamentals of formal experimentation, randomization, and the use of control groups are introduced in the same manner, followed by the presentation and explanation of common (and later, more advanced) designs. Replete with synopses of examples from the journal literature and supplemented by 25 experimental principles, this book is designed to serve as an interdisciplinary supplementary text for research-methods courses in the educational, psychological, behavioral, social, and health sciences. It also serves as an excellent primary text for methods seminar courses.