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76 results in Psychology research methods and statistics

Page 1 of 4

The Cambridge Handbook of Behavioural Data Science
  • Edited by Ganna Pogrebna, Thomas T. Hills
  • Coming soon
  • Expected online publication date:
    April 2026
    Print publication:
    30 April 2026
  • The Cambridge Handbook of Behavioural Data Science offers an essential exploration of how behavioural science and data science converge to study, predict, and explain human, algorithmic, and systemic behaviours. Bringing together scholars from psychology, economics, computer science, engineering, and philosophy, the Handbook presents interdisciplinary perspectives on emerging methods, ethical dilemmas, and real-world applications. Organised into modular parts-Human Behaviour, Algorithmic Behaviour, Systems and Culture, and Applications—it provides readers with a comprehensive, flexible map of the field. Covering topics from cognitive modelling to explainable AI, and from social network analysis to ethics of large language models, the Handbook reflects on both technical innovations and the societal impact of behavioural data, and reinforces concepts in online supplementary materials and videos. The book is an indispensable resource for researchers, students, practitioners, and policymakers who seek to engage critically and constructively with behavioural data in an increasingly digital and algorithmically mediated world.

The Psychologist's Companion
  • A Guide to Professional Success for Students, Teachers, and Researchers
  • 7th edition
  • Robert J. Sternberg, Karin Sternberg, Ophélie Allyssa Desmet
  • Coming soon
  • Expected online publication date:
    December 2025
    Print publication:
    31 December 2025
  • In the evolving landscape of psychological research and communication, The Psychologist's Companion, stands as the definitive guide supporting students, young professionals, and researchers in psychology at all stages of their careers. This seventh edition presents new and updated chapters covering a wide range of topics essential for success in psychology, including planning and writing research papers, presenting data effectively, evaluating one's own work, writing grant proposals, giving talks and presentations, finding a book publisher, navigating job interviews, and more! Serving as an invaluable resource for improving both written and oral communication skills in academic psychology, the content is structured as a step-by-step manual focusing on practical skills and contemporary issues. It guides readers through various tasks encountered during psychological research and academic life. Whether you're crafting your first paper or seeking to enhance your scholarly impact, this book provides the tools and knowledge to excel in today's competitive academic environment.

The Psychology of Human Temporality
  • David Gilden
  • Coming soon
  • Expected online publication date:
    December 2025
    Print publication:
    31 December 2025
  • Understanding human temporality is a theoretical and experimental challenge, requiring ingenious ways to capture the manner in which time enters and structures human experience. This book bridges music, physics, and experimental psychology to present a unique perspective on the experience of time that is rooted in both physical theory and Gestalt psychology. Featuring a novel framework based on the idea that people sense time indirectly through the visceral feeling that time passage generates, it draws on the authors decades of research in cognitive psychology to present a unique perspective on this topic. It will be of interest to students, researchers, and anyone seeking deeper insight into how the mind and body interact to shape personal experience and the world we inhabit.

Elements of Structural Equation Models (SEMs)
  • Kenneth A. Bollen
  • Coming soon
  • Expected online publication date:
    November 2025
    Print publication:
    30 November 2025
  • Elements of Structural Equation Models (SEMs) blends theoretical foundations with practical applications, serving as both a learning tool and a lasting reference. Synthesizing material from diverse sources, including the author's own contributions, it provides a rigorous yet accessible guide for graduate students, faculty, and researchers across social, behavioral, health, and data sciences. The book covers essential SEM concepts – model assumptions, identification, estimation, and diagnostics – while also addressing advanced topics often overlooked, such as Bayesian SEMs, model-implied instrumental variables, and categorical variables. Readers will gain insights into missing data, longitudinal models, and comparisons with Directed Acyclic Graphs (DAGs). By presenting complex technical content in a clear, structured way, this authoritative resource deepens readers' understanding of SEMs, making it an indispensable guide for both newcomers and experts seeking a definitive treatment of the field.

Big Data in the Psychological Sciences
  • Wilma A. Bainbridge
  • Coming soon
  • Expected online publication date:
    October 2025
    Print publication:
    31 October 2025
  • Cutting-edge computational tools like artificial intelligence, data scraping, and online experiments are leading to new discoveries about the human mind. However, these new methods can be intimidating. This textbook demonstrates how Big Data is transforming the field of psychology, in an approachable and engaging way that is geared toward undergraduate students without any computational training. Each chapter covers a hot topic, such as social networks, smart devices, mobile apps, and computational linguistics. Students are introduced to the types of Big Data one can collect, the methods for analyzing such data, and the psychological theories we can address. Each chapter also includes discussion of real-world applications and ethical issues. Supplementary resources include an instructor manual with assignment questions and sample answers, figures and tables, and varied resources for students such as interactive class exercises, experiment demos, articles, and tools.

Diffusion Process Models of Decision Making
  • Fundamental Processes
  • Volume 1
  • Philip L. Smith, Roger Ratcliff
  • Coming soon
  • Expected online publication date:
    October 2025
    Print publication:
    31 October 2025
  • Diffusion decision models are widely used to characterize the cognitive and neural processes involved in making rapid decisions about objects and events in the environment. These decisions, which are made hundreds of times a day without prolonged deliberation, include recognition of people and things as well as real-time decisions made while walking or driving. Diffusion models assume that the processes involved in making such decisions are noisy and variable and that noisy evidence is accumulated until there is enough for a decision. This volume provides the first comprehensive treatment of the theory, mathematical foundations, numerical methods, and empirical applications of diffusion process models in psychology and neuroscience. In addition to the standard Wiener diffusion model, readers will find a detailed, unified treatment of the cognitive theory and the neural foundations of a variety of dynamic diffusion process models of two-choice, multiple choice, and continuous outcome decisions.

Research Methods and Applied Statistics
  • A Practical Guide to Conducting Research
  • Anthony J. Girasoli
  • Coming soon
  • Expected online publication date:
    September 2025
    Print publication:
    31 August 2025
  • Students have an almost insurmountable task in understanding statistics in the psychological sciences and applying them to a research study. This textbook tackles this source of stress by guiding students through the research process, start to finish, from writing a proposal and performing the study, to analysing the results and creating a report and presentation. This truly practical textbook explains psychology research methods in a conversational style, with additional material of interest placed in focus boxes alongside, so that students don't lose their way through the steps. Every step is detailed visually with processes paralleled in both SPSS and R, allowing instructors and students to learn both statistical packages or to bridge from one to the other. Students perform hands-on statistical exercises using real data, and both qualitative and mixed-methods research are covered. They learn effective ways to present information visually, and about free tools to collect and analyse data.

Foundations of MATLAB Programming for Behavioral Sciences
  • With Applications
  • Maxwell Mansolf
  • Coming soon
  • Expected online publication date:
    September 2025
    Print publication:
    07 August 2025
  • This textbook introduces the fundamentals of MATLAB for behavioral sciences in a concise and accessible way. Written for those with or without computer programming experience, it works progressively from fundamentals to applied topics, culminating in in-depth projects. Part I covers programming basics, ensuring a firm foundation of knowledge moving forward. Difficult topics, such as data structures and program flow, are then explained with examples from the behavioral sciences. Part II introduces projects for students to apply their learning directly to real-world problems in computational modelling, data analysis, and experiment design, with an exploration of Psychtoolbox. Accompanied by online code and datasets, extension materials, and additional projects, with test banks, lecture slides, and a manual for instructors, this textbook represents a complete toolbox for both students and instructors.

Introductory Grantology
  • A Guide for Pursuing Competitive Grants
  • Zheng Yan
  • Coming soon
  • Expected online publication date:
    August 2025
    Print publication:
    21 August 2025
  • This book addresses the lack of systematic training in journal publication and grant pursuit for new scholars, two key skills in today's academic landscape. It introduces 'grantology,' the science of pursuing grants, providing practical, evidence-based strategies. Structured like a graduate course, each chapter follows a five-step cognitive sequence based on Daniel Kahneman's intuitive judgment theory. The book explores over fifty real-life cases, draws from nearly two hundred research articles, and compares grantology with journalology. With scientific insights and actionable advice, this guide supports junior researchers, graduate students, and new grant writers in developing the skills needed to pursue competitive grants and advance their careers.

Direction Dependence Analysis
  • Foundations and Statistical Methods
  • Wolfgang Wiedermann, Alexander von Eye
  • Coming soon
  • Expected online publication date:
    July 2025
    Print publication:
    14 August 2025
  • While regression analysis is widely understood, it falls short in determining the causal direction of relationships in observational data. In this groundbreaking volume, Wiedermann and von Eye introduce Direction Dependence Analysis (DDA), a novel method that leverages variable information often overlooked by traditional techniques, such as higher-order moments like skewness and kurtosis. DDA reveals the asymmetry properties of regression and correlation, enabling researchers to evaluate competing causal hypotheses, assess the roles of variables in causal flows, and develop statistical methods for testing causal direction. This book provides a comprehensive formal description of DDA, illustrated with both artificial and real-world data examples. Additionally, readers will find free software implementations of DDA, making this an essential resource for researchers seeking to enhance their understanding of causal relationships in data analysis.

Rethinking Clinical Research
  • Methodology and Ethics
  • Karen B. Schmaling, Robert M. Kaplan
  • Published online:
    13 March 2025
    Print publication:
    20 March 2025
  • This book provides a comprehensive analysis of biases inherent in contemporary clinical research, challenging traditional methodologies and assumptions. Aimed at students, professionals, and science enthusiasts, the book delves into fundamental principles, research tools, and ethics. It is organized in three sections: The first section covers fundamentals including framing clinical research questions, core research tools, and clinical research ethics. The second section discusses topics relevant to clinical research, organized according to their relevance in the development of a clinical study. Chapters within this section examine the strengths and limitations of traditional and alternative methods, ethical issues, and patient-centered consequences. The third section presents four in-depth case examples, illustrating issues across diverse health conditions and treatments: gastroesophageal reflux disease, hypercholesterolemia, screening for breast cancer, and depression. This examination encourages readers to critically evaluate the methodologies and assumptions underlying clinical research, promoting a nuanced understanding of evidence production in the health sciences.

Social Behavioral Statistics
  • Roberto R. Heredia, Richard D. Hartley
  • Published online:
    13 January 2025
    Print publication:
    28 November 2024
  • Focusing on practical application, this textbook provides clear and concise explanations of statistical tests and techniques that students can apply in real-world situations. It has a dual emphasis: firstly, on doing statistics, and secondly, on understanding statistics, to do away with the mindset that statistics is difficult. Procedural explanations are provided so students know how to apply particular statistical tests and techniques in practical research situations. Conceptual understanding is encouraged to ensure students know not only when and how to apply appropriate techniques, but also why they are using them. Ancillary resources are available including sample answers to exercises, PowerPoint teaching slides, instructor manual, and a test bank. Illustrative figures, real-world data, practice exercises, and software instruction make this an essential resource for mastering statistics for undergraduate and graduate students in the social and behavioral sciences.

The Cambridge Handbook of Research Methods and Statistics for the Social and Behavioral Sciences
  • Volume 2: Performing Research
  • Volume 2
  • Edited by John E. Edlund, Austin Lee Nichols
  • Published online:
    12 December 2024
    Print publication:
    19 December 2024
  • In a time where new research methods are constantly being developed and science is evolving, researchers must continually educate themselves on cutting-edge methods and best practices related to their field. The second of three volumes, this Handbook provides comprehensive and up-to-date coverage of a variety of issues important in developing, designing, and collecting data to produce high-quality research efforts. First, leading scholars from around the world provide an in depth explanation of various advanced methodological techniques. In section two, chapters cover general important methodological considerations across all types of data collection. In the third section, the chapters cover self-report and behavioral measures and their considerations for use. In the fourth section, various psychological measures are covered. The final section of the handbook covers issues that directly concern qualitative data collection approaches. Throughout the book, examples and real-world research efforts from dozens of different disciplines are discussed.

A Practical Guide to Data Analysis Using R
  • An Example-Based Approach
  • John H. Maindonald, W. John Braun, Jeffrey L. Andrews
  • Published online:
    11 May 2024
    Print publication:
    30 May 2024
  • Using diverse real-world examples, this text examines what models used for data analysis mean in a specific research context. What assumptions underlie analyses, and how can you check them? Building on the successful 'Data Analysis and Graphics Using R,' 3rd edition (Cambridge, 2010), it expands upon topics including cluster analysis, exponential time series, matching, seasonality, and resampling approaches. An extended look at p-values leads to an exploration of replicability issues and of contexts where numerous p-values exist, including gene expression.Developing practical intuition, this book assists scientists in the analysis of their own data, and familiarizes students in statistical theory with practical data analysis. The worked examples and accompanying commentary teach readers to recognize when a method works and, more importantly, when it doesn't. Each chapter contains copious exercises. Selected solutions, notes, slides, and R code are available online, with extensive references pointing to detailed guides to R.

Statistics Using Stata
  • An Integrative Approach
  • 3rd edition
  • Sharon Lawner Weinberg, Sarah Knapp Abramowitz, Daphna Harel
  • Published online:
    26 January 2024
    Print publication:
    30 November 2023
  • Statistics Using Stata uses a highly accessible and lively writing style to seamlessly integrate the learning of the latest version of Stata (17) with an introduction to applied statistics using real data in the behavioral, social, and health sciences. The text is comprehensive in its content coverage and is suitable at undergraduate and graduate levels. It requires knowledge of basic algebra, but no prior coding experience. It is uniquely focused on the importance of data management as an underlying and key principle of data analysis. It includes a .do-file for each chapter, that was used to generate all figures, tables, and analyses for that chapter. These files are intended as models to be adapted and used by readers in conducting their own research. Additional teaching and learning aids include solutions to all end-of-chapter exercises and PowerPoint slides to highlight the important take-aways of each chapter.

Pragmatism and Methodology
  • Doing Research That Matters with Mixed Methods
  • Alex Gillespie, Vlad Glăveanu, Constance de Saint Laurent
  • Published online:
    04 January 2024
    Print publication:
    25 January 2024
  • Taking a pragmatist approach to methods and methodology that fosters meaningful, impactful, and ethical research, this book rises to the challenge of today's data revolution. It shows how pragmatism can turn challenges, such as the abundance and accumulation of big qualitative data, into opportunities. The authors summarize the pragmatist approach to different aspects of research, from epistemology, theory, and questions to ethics, as well as data collection and analysis. The chapters outline and document a new type of mixed methods design called 'multi-resolution research,” which serves to overcome old divides between quantitative and qualitative methods. It is the ideal resource for students and researchers within the social and behavioural sciences seeking new ways to analyze large sets of qualitative data. This book is also available as Open Access on Cambridge Core.

Statistics Using R
  • An Integrative Approach
  • 2nd edition
  • Sharon Lawner Weinberg, Daphna Harel, Sarah Knapp Abramowitz
  • Published online:
    07 December 2023
    Print publication:
    07 December 2023
  • Statistics Using R introduces the most up-to-date approaches to R programming alongside an introduction to applied statistics using real data in the behavioral, social, and health sciences. It is uniquely focused on the importance of data management as an underlying and key principle of data analysis. It includes an online R tutorial for learning the basics of R, as well as two R files for each chapter, one in Base R code and the other in tidyverse R code, that were used to generate all figures, tables, and analyses for that chapter. These files are intended as models to be adapted and used by readers in conducting their own research. Additional teaching and learning aids include solutions to all end-of-chapter exercises and PowerPoint slides to highlight the important take-aways of each chapter. This textbook is appropriate for both undergraduate and graduate students in social sciences, applied statistics, and research methods.

Thinking and Deciding
  • 5th edition
  • Jonathan Baron
  • Published online:
    22 September 2023
    Print publication:
    10 August 2023
  • The fifth edition of the classic text Thinking and Deciding updates the broad overview of the field of judgments and decisions offered in previous editions. It covers the normative standards used to evaluate conclusions, such as logic, probability, and various forms of utility theory. It explains descriptive accounts of departures from these standards, largely in terms of principles of cognitive psychology, emphasizing the distinction between search processes and inferences. Chapters cover decisions under risk, decision analysis, moral decisions and social dilemmas, and decisions about the future. Although the book assumes no particular prerequisites beyond introductory high-school algebra, it is most suited to advanced undergraduates, early graduate students, and active researchers in related fields, such as business, politics, law, medicine, economics, and philosophy.

Research Design in Clinical Psychology
  • 6th edition
  • Alan E. Kazdin
  • Published online:
    25 August 2023
    Print publication:
    07 September 2023
  • Gain a thorough understanding of the entire research process – developing ideas, selecting methods, analyzing and communicating results – in this fully revised and updated textbook. The sixth edition comprises the latest developments in the field, including the use of technology and web-based methods to conduct studies, the role of robots and artificial intelligence in designing and evaluating research, and the importance of diversity in research to inform results that reflect the society we live in. Designed to inspire the development of future research processes, this is the perfect textbook for graduate students and professionals in research methods and research design in clinical psychology.

The General Linear Model
  • A Primer
  • Alexander von Eye, Wolfgang Wiedermann
  • Published online:
    15 June 2023
    Print publication:
    29 June 2023
  • General Linear Model methods are the most widely used in data analysis in applied empirical research. Still, there exists no compact text that can be used in statistics courses and as a guide in data analysis. This volume fills this void by introducing the General Linear Model (GLM), whose basic concept is that an observed variable can be explained from weighted independent variables plus an additive error term that reflects imperfections of the model and measurement error. It also covers multivariate regression, analysis of variance, analysis under consideration of covariates, variable selection methods, symmetric regression, and the recently developed methods of recursive partitioning and direction dependence analysis. Each method is formally derived and embedded in the GLM, and characteristics of these methods are highlighted. Real-world data examples illustrate the application of each of these methods, and it is shown how results can be interpreted.

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