Books and media reviews

The following items are currently available. There is no fee but the reviewer keeps the book, except when publishers make an ebook available for limited time.

Please contact the reviews editor Kuldeep Kumar ( to express an interest in reviewing one of the listed books and to receive a copy for review. The editor will arrange for you to be invited to submit your finished review to the ScholarOne system for Series A and provide you with full instructions on how to make your submission.

  • Books available
    Aarons, Haydn; A Practical Introduction to Survey Design; Sage Publishing
    Abramovich, Felix; Ritov, Ya'acov; Statistical Theory: A Concise Introduction Second Edition; CRC Press
    A. Cook, Jonathan; An Introduction to Clinical Trials; OUP
    Achen, Christopher H.; The Statistical Analysis of Quasi-Experiments, First Edition; Wiley
    Ahmed, Syed Ejaz; Post-Shrinkage Strategies in Statistical and Machine Learning for High Dimensional Data; CRC Press
    Akashi, Fumiya; Diagnostic Methods in Time Series; Springer
    Alby, Tom; Data Science in Practice; CRC Press
    Alexander, Rohan; Telling Stories with Data: With Applications in R; CRC Press
    Almudevar, Anthony; Theory of Statistical Inference;
    Al-Murrani, Waleed ; General, Biological and Biomedical Statistics; Troubador Publishing
    Ariza, Medina; Crime Mapping and Spatial Data Analysis using R; CRC Press
    Armstrong, David A.; Presenting Statistical Results Effectively; Sage Publishing
    Aslam, Muhammad; Introduction to Statistical Process Control; Wiley
    Awe, Olawale; Promoting Statistical Practice and Collaboration in Developing Countries; Chapman & Hall/CRC
    Aydede, Yigit; Machine Learning Toolbox for Social Scientists: Applied Predictive Analytics with R; CRC Press
    Bailer, A.; Statistical Programming in SAS; Chapman and Hall/CRC Press
    Balakrishnan, Narayanaswamy .; Accelerated Life Testing of One-shot Devices: Data Collection and Analysis; Wiley
    Banks, David L.; Handbook of Forensic Statistics; Chapman and Hall/CRC Press
    Barbu, Vlad Stefan.; Statistical Topics and Stochastic Models for Dependent Data with Applications; Wiley
    Beggs, C.; Soccer Analytics: An Introduction Using R​; CRC Press
    Berger, J.; Handbook of Bayesian, Fiducial, and Frequentist Inference; CRC Press
    Beuzen, Tomas; Python Packages; Chapman & Hall/CRC Press
    Bischl, B.; Applied Machine Learning Using mlr3 in R; CRC Press
    Bittelli, Marco; Olmi, Roberto; and Rosa, Rodolfo; Random Process Analysis With R; OUP
    Bonnell, Jerry; Exploring Data Science with R and the Tidyverse: A Concise Introduction; CRC Press
    Bose, Arup; Random Matrices and Non-Commutative Probability;
    Bousquet, Nicolas ; Extreme Value Theory with Applications to Natural Hazards; Springer
    Braun, Murdoch.; A First Course in Statistical Programming with R; Cambridge University Press
    Brémaud, Pierre; Probability Theory and Stochastic Processes; Springer
    Brito, Paula; Analysis of Distributional Data; Chapman & Hall/CRC
    Brookfield, Charlotte; Using Microsoft Excel for Social Research; Sage Publishing
    Broström, Göran; Event History Analysis with R;
    Brus, Dick J; Spatial Sampling with R; CRC Press
    Buchbinder, Iosif L.; Shapiro, Ilya.; Introduction to Quantum Field Theory with Applications to Quantum Gravity; Oxford University Press
    Campbell, Michael J.; Statistics at Square Two: Understanding Modern Statistical Applications in Medicine; Wiley
    Chen, Ding-Geng; Structural Equation Modeling Using R/SAS: A Step-by-Step Approach with Real Data Analysis; CRC Press
    Chen, Hua Yun; Semiparametric Odds Ratio Model and Its Applications;
    Chiang, S.; Statistical Methods in Epilepsy; CRC Press 
    Christy Chuang-Stein; Quantitative Decisions in Drug Development; Springer
    Chun, Asaph Young; Administrative Records for Survey Methodology; Wiley
    Cocco, Simona; From Statistical Physics to Data-Driven Modelling; OUP
    Coene, John; Javascript for R; Chapman & Hall/CRC Press
    Cole, Diana; Parameter Redundancy and Identifiability; Chapman and Hall/CRC Press
    Collard, Jean-Francois; Hands-On Data Analysis in R for Finance; CRC Press
    Comber, Lex ; Geographical Data Science and Spatial Data Analysis; Sage Publishing
    Coqueret, Guillaume; Machine Learning for Factor Investing: Python Version; CRC Press
    Cortez, Paulo; Modern Optimization with R; Springer
    Crainiceanu, C.M.; Functional Data Analysis with R; CRC Press
    Cui, Xinping; Handbook of Multiple Comparisons;
    Dai, Harrison.; Processing Networks; Cambridge University Press
    Daniels, Michael J.; Bayesian Nonparametrics for Causal Inference and Missing Data; CRC Press
    Davidson, James; Stochastic Limit Theory An Introduction for Econometricians; Oxford University Press
    De Uña-Álvarez, Jacobo; The Statistical Analysis of Doubly Truncated Data: With Applications in R; Wiley
    Debowski, Lukasz.; Information Theory Meets Power Laws: Stochastic Processes and Language Models; Wiley
    DeVellis, Robert F.  ; Scale Development: Theory and Applications; Sage Publishing
    Dikta, Gerhard; Bootstrap Methods With Applications in R; Springer
    Dimotikalis, Yannis; Applied Modeling Techniques and Data Analysis 2: Financial, Demographic, Stochastic and Statistical Models and Methods; Wiley
    Ding-Geng (Din) Chen; Statistical Regression Modeling with R; Springer
    Dinov, Evo; Data Science – Time Complexity, Inferential Uncertainty, and Spacekime Analytics; De Gruyter
    Doganaksoy, Necip; Achieving Product Reliability: A Key to Business Success; Chapman &Hall/CRC Press
    Emam, Moataz H.; Covariant Physics; Oxford University Press
    Fagan, Brennen; Quantifying Counterfactual Military History; CRC Press
    Faraway, Julian J.; Linear Models with Python; Chapman and Hall/CRC Press
    Faya, Paul; Pourmohamad, Tony; Case Studies in Bayesian Methods for Biopharmaceutical CMC; CRC Press
    Filipiak, Katarzyna; Multivariate, Multilinear and Mixed Linear Models; Springer
    Field, Andy; An Adventure in Statistics: The Reality Enigma; Sage Publications
    Fraser, Christophe; Grassly, Nicholas C.; Infectious Disease Epidemiology; Oxford University Press
    Friendly, Michael; A History of Data Visualization and Graphic Communication; Harvard University Press
    Garcia Ceja, Enrique; Behavior Analysis with Machine Learning Using R;
    Gates, Kathleen M; Intensive Longitudinal Analysis of Human Processes; CRC Press
    Gilliland, Michael; Business Forecasting: The Emerging Role of Artificial Intelligence and Machine Learning; Wiley
    Giné, Nickl; Mathematical Foundations of Infinite-Dimensional Statistical Models; Cambridge University Press
    Glaz, Barry; Applied Statistics in Agricultural, Biological, and Environmental Sciences; Wiley
    Goad, Carla L.; SAS Programming for Elementary Statistics: Getting Started; Chapman and Hall/CRC Press
    Gosser, David; R for Quantitative Chemistry; CRC Press
    Granjon, David; Outstanding User Interfaces with Shiny​; CRC Press
    Greselin, Francesca, Vichi, Maurizio, Deldossi, Laura, and Bagnato, Luca; Statistical Learning of Complex Data; Springer
    Grosser, Malte; Advanced R Solutions; Chapman & Hall/CRC Press
    Gupta, Bhisham C.; Statistical Quality Control: Using MINITAB, R, JMP and Python; Wiley
    Heath, A.; Value of Information for Healthcare Decision-Making; CRC Press
    Harrer, Mathias.; Doing Meta-Analysis with R: A Hands-On Guide; Chapman & Hall/CRC Press
    Harrison, Ewen; R for Health Data Science; Chapman and Hall/CRC Press
    Hector, Andrew; The New Statistics with R; Oxford University Press
    Hector Andy; The New Statistics with R An Introduction for Biologists; Oxford University Press
    Helsper, Ellen; The Digital Disconnect; Sage Publishing
    Hesamian, Gholamreza; Fuzzy Statistical Inferences Based on Fuzzy Random Variables; Chapman & Hall/CRC Press
    Henderson, Peter A.; Southwood's Ecological Methods; Oxford University Press
    Hill, Craig A.; Big Data Meets Survey Science: A Collection of Innovative Methods; Wiley
    Hirschauer, Norbert ; “Fundamentals of Statistical Inference – What is the Meaning of Random Error” that will be published  in the “SpringerBriefs in Applied Statistics and Econometrics” (SBASE), ; Springer Briefs (SBASE)                              
    Inchausti, Pablo; Statistical Modeling With R; OUP
    Jansen, Maarten; Wavelets from a Statistical Perspective; Chapman & Hall/CRC Press
    Julious, Steven A.; Sample Sizes for Clinical Trials 2nd Edition; CRC Press
    Kabacoff, R.; Modern Data Visualization with R; CRC Press
    Kirk, Andy; Data Visualisation: A Handbook for Data Driven Design, 2nd Edition; Sage
    Kolassa, Stephan; Demand Forecasting for Executives and Professionals; CRC Press
    Koroliouk, Dmitri.; Dynamics of Statistical Experiments; Wiley
    Korosteleva, Olga; Stochastic Processes with R: An Introduction; Chapman & Hall/CRC Press
    Krijnen, Wim P.; Wit, Ernst C.; Computational and Statistical Methods for Chemical Engineering; CRC Press
    Krishna Kumar Mohbey; Predictive Analytics Using Statistics and Big Data: Concepts and Modeling; Bentham Publications.
    Krippendorff, Klaus; The Reliability of Generating Data; CRC Oress
    Kronthaler, Franz; Data Analysis with RStudio; Springer
    Krzysztof Jajuga; Data Analysis and Classification; Springer
    Kulas, John T.; IBM SPSS Essentials: Managing and Analyzing Social Sciences Data, 2nd Edition; Wiley
    Lauritzen, Steffen; Fundamentals of Mathematical Statistics; CRC Press
    Lawson, John; An Introduction to Acceptance Sampling and SPC with R; Chapman and Hall/CRC Press
    Lê Cao, Kim-Anh; Multivariate Data Integration Using R: Methods and Applications with the mixOmics Package;
    Lee, Peter M.; Bayesian Statistics: An Introduction, 3rd Edition; Wiley
    Lee, Sang Joon; Methodologies in Biosimilar Product Development; Chapman & Hall/CRC Press
    Leemis, Larry; Mathematical Statistics; Taylor and Francis
    Leemis, Larry; Probability, 2nd Edition; Taylor and Francis
    Leemis, Larry; Learning Base R Second Edition
    Liang, Faming; Sparse Graphical Modeling for High Dimensional Data: A Paradigm of Conditional Independence Tests; CRC Press
    Lighton, John R. B.; Measuring Metabolic Rates; Oxford University Press
    Limnios, Nikolaos.; Statistical Methods and Modeling of Seismogenesis; Wiley
    Lin, Hui; Li, Ming; Practitioner’s Guide to Data Science; CRC Press
    Lin, Sarah; Scott, Dorris; Hands-On Data Science for Librarians; CRC Press
    Lin, Shili; Bioinformatics Methods: From Omics to Next Generation Sequencing; CRC Press
    Lohr, Sharon L.; SAS® Software Companion for Sampling: Design and Analysis, Third Edition;
    Longford, Nicholas T.; Statistics for Making Decisions; Chapman &Hall/CRC Press
    Lu, Yan; R Companion for Sampling: Design and Analysis, Third Edition;
    Lyubchich, Vyacheslav; Evaluating Climate Change Impacts; Chapman and Hall/CRC Press
    Makrides, Andreas; Data Analysis and Applications 3: Computational, Classification, Financial, Statistical and Stochastic Methods; Wiley
    Mallinckrodt, Craig; Building Your Career as a Statistician: A Practical Guide to Longevity, Happiness, and Accomplishment; CRC Press
    Martinková, Patricia; Computational Aspects of Psychometric Methods: With R; CRC Press
    Matter, Ulrich; Big Data Analytics: A Guide to Data Science Practitioners Making the Transition to Big Data; CRC Press
    Mattingly, William; Introduction to Python for Humanists; CRC Press
    Mavrakakis, Miltiadis C.; Probability and Statistical Inference: From Basic Principles to Advanced Models; Chapman &Hall/CRC Press
    McNulty, Keith; Handbook of Graphs and Networks in People Analytics: With Examples in R and Python; Chapman & Hall/CRC
    McLevey, John; Doing Computational Social Science; Sage Publishing
    Meester, Slooten.; Probability and Forensic Evidence; Cambridge University Press
    Mehmetoglu, Mehmet.; Structural Equation Modelling with Partial Least Squares Using Stata and R; Chapman and Hall/CRC Press
    Melamed, David; Applications of Regression for Categorical Outcomes Using R; CRC Press
    Mo, Wenhui; Reliability Calculations with the Stochastic Finite Element; Bentham Publications.
    Mohbey, KK(ed).; Predictive Analytics Using Statistics and Big Data: Concepts and Modeling; Bentham Publications
    Møller, J.K.; Statistical Modelling of Occupant Behaviour; CRC Press
    Monaghan, Lee; Key Concepts in Medical Sociology; Sage Publishing
    Moody, Patricia; Applied Regression and ANOVA Using SAS; Chapman & Hall/CRC
    Morrison.; Uncertainty Analysis for Engineers and Scientists; Cambridge University Press
    Mu Zhu; Essential Statistics for Data Science: Ebook; OUP
    Mueller, John Paul.; Data Science Programming All-in-One For Dummies; Wiley
    Nelson, Michael; Statistics in Nutrition and Dietetics; Wiley
    Niewiadomska-Bugaj, Magdalena; Probability and Statistical Inference, 3rd Edition; Wiley
    Nolan, Deborah; Communicating with Data: The Art of Writing for Data Science; Oxford University Press
    Oakland, John S., Oakland, Robert J. and Turner, Michael A.; Total Quality Management and Operational Excellence: Text with Cases, 5th edn; Routledge
    O’Brien, Daniel T.; Urban Informatics: Urban Informatics; CRC Press
    Otieno Okello, Gabriel; Urban Informatics: Urban Informatics; CRC Press
    Paradis, Emmanuel; Population Genomics with R; Chapman and Hall/CRC Press
    Pawitan, Y.; Philosophies, Puzzles and Paradoxes: A Statistician’s Search for Truth; CRC Press
    Pebesma, Edzer; Bivand, Roger; Spatial Data Science: With Applications in R; CRC Press
    Peng, Shige; Nonlinear Expectations and Stochastic Calculus under Uncertainty; Springer
    Peng, Yingwei; Cure Models: Methods, Applications, and Implementation; Chapman and Hall/CRC Press
    Petchey, Owen L.; Beckerman, Andrew P.; Cooper, Natalie; Childs, Dylan Z.; Insights from Data with R; Oxford University Press
    Peter Filzmoser; Advances in Compositional Data Analysis; Springer
    Pradhan, Vivek; Confidence Intervals for Discrete Data in Clinical Research;
    Privault, Nicolas; Introduction to Stochastic Finance with Market Examples; CRC Press
    Pourmohamad, Tony ; Bayesian Optimization with Application to Computer Experiments; Springer
    Prügel-Bennett, Adam; The Probability Companion for Engineering and Computer Science; Cambridge University Press
    Qian, Song S.; DuFour, Mark R.; Alameddine, Ibrahim; Bayesian Applications in Environmental and Ecological Studies with R and Stan; CRC Press
    Quirk, Thomas J.; Excel 2019 for Engineering Statistics; Springer
    Quirk, Thomas J. ; Excel 2019 for Environmental Sciences Statistics; Springer
    Quirk, Thomas J.; Excel 2019 for Marketing Statistics; Springer
    Rabbee, Nusrat; Biomarker Analysis in Clinical Trials with R;
    Ram Gopal; Foundations of Programming, Statistics, and Machine Learning for Business Analytics; Sage Publications
    Rausand, Marvin; System Reliability Theory: Models, Statistical Methods, and Applications, 3rd Edition; Wiley
    Ravishanker, Nalini; A First Course in Linear Model Theory;
    Ravishanker, Nalini; Raman, Balaji; Soyer, Refik;  Dynamic Time Series Models using R-INLA: An Applied Perspective; CRC Press
    Reilly, Marie; Controlled Epidemiological Studies; CRC Press
    Rey, Sergio; Arribas-Bel; Geographic Data Science with Python; CRC Press
    Rhinehart, R. Russell; Applied Engineering Statistics;
    Rivera, Roberto ; Principles of Managerial Statistics and Data Science; Wiley
    Russell, Matthew; Statistics in Natural Resources: Applications in R; CRC Press
    Saiyidi Mat Roni; Data Analysis with SPSS for Survey-based Research; Springer
    Sarka, Dejan; Advanced Analytics with Transact-SQL; Springer
    Särkkä, Simo; Bayesian Filtering and Smoothing; Cambridge University Press
    Scheps, Swain; Sports Betting For Dummies; Wiley
    Schouten, Barry; Mixed-Mode Official Surveys: Design and Analysis; Chapman & Hall/CRC Press
    Scott, David W.; Statistics: A Concise Mathematical Introduction for Students, Scientists, and Engineers; Wiley
    Scrucca, Luca; Model-Based Clustering, Classification, and Density Estimation Using mclust in R; CRC Press
    Scutari, Marco; Bayesian Networks: With Examples in R; Chapman & Hall/CRC Press
    Seif El-Nasr, Magy ; Game Data Science; Oxford University Press
    Sethna, James P.; Statistical Mechanics: Entropy, Order Parameters, and Complexity; Oxford University Press
    Shea, J.M.; Foundations of Data Science with Python; CRC Press
    Somnath Datta; Statistical Analysis of Microbiome Data; Springer
    Sunil Rao, J.; Statistical Methods in Health Disparity Research; CRC Press
    Sverdlov, Oleksandr; van Dam, Joris; Digital Therapeutics: Strategic, Scientific, Developmental, and Regulatory Aspects; CRC Press
    Szekely, Gobor J; The Energy of Data and Distance Correlation; CRC Press
    Tadesse, Mahlet; Handbook of Bayesian Variable Selection;
    Tamhane, Ajit C.; Predictive Analytics: Parametric Models for Regression and Classification Using R; Wiley
    Tan, Frans E.S.; Jolani, Shahab; Applied Linear Regression for Longitudinal Data: With an Emphasis on Missing Observations; CRC Press
    Tang, Wan; Applied Categorical and Count Data Analysis 2nd Edition; CRC Press
    Tartakovsky, Alexander; Sequential Change Detection and Hypothesis Testing; Chapman and Hall/CRC Press
    Thomas, Amos Owen; Shadow Trades-The Dark Side of Global Business; Sage Publishing
    Thompson Klein, Julie; Beyond Interdisciplinarity; Oxford University Press
    Thornett, Michael; Mean Likelihood Theory; Self publication
    Thorson, J.; Spatio-Temporal Models for Ecologists; CRC Press
    Tille, Yves; Sampling and Estimation from Finite Populations; Wiley
    Urdinez, Francisco; R for Political Data Science: A Practical Guide; Chapman and Hall/CRC Press
    Vassiliou, P.-C.G.; Non-Homogeneous Markov Chains and Systems: Theory and Applications; CRC Press
    Walden, Andrew T. and Percival, Donald B.; Spectral Analysis for Univariate Time Series; Cambridge University Press  
    Walker, Kyle; Analyzing US Census Data: Methods, Maps, and Models in R; CRC Press
    Walters, Lee; Conditionals, Paradox, and Probability: Themes from the Philosophy of Dorothy Edgington; Oxford University Press
    Wang, Lily; Data Science for Infectious Disease Data Analytics: An Introduction with R; CRC Press
    Wang, Xinkun; Next-Generation Sequencing Data Analysis Second Edition; CRC Press
    Wang, You-Gan; Analysis of Longitudinal Data with Examples; Chapman & Hall/CRC Press              
    Wang, William; Quantitative Methodologies and Process for Safety Monitoring and Ongoing Benefit Risk Evaluation;
    West, Brady; Linear Mixed Models: A Practical Guide Using Statistical Software; Chapman & Hall/CRC
    Whitmore, Nathan; R for Conservation and Development Projects: A Primer for Practitioners; Chapman and Hall/CRC Press
    Wiedermann, Wolfgang; Direction Dependence in Statistical Modeling: Methods of Analysis; Wiley
    Wilson, Jeffrey; Statistical Analytics for Health Data Science with SAS and R; CRC Press
    Woodward, Wayne A.; Sadler, Bivin Phillip; Robertson, Stephen; Time Series for Data Science: Analysis and Forecasting; CRC Press
    Worch, Thierry; Data Science for Sensory and Consumer Scientists; CRC Press
    Wu, Jianrong; Single-Arm Phase II Survival Trial Design; Chapman & Hall/CRC Press
    Wu, Rongling; Quantitative Methods for Precision Medicine: Pharmacogenomics in Action​; CRC Press
    Wu, D.; Probability Modeling and Statistical Inference in Cancer Screening; CRC Press
    Xu, Jun; Modern Applied Regressions: Bayesian and Frequentist Analysis of Categorical and Limited Response Variables with R and Stan​; CRC Press
    Yang, Bo; Drug Development for Rare Diseases; CRC Press
    Yu, Guangchuang; Data Integration, Manipulation and Visualization of Phylogenetic Trees; CRC Press
    Zakeri, Saeed; A Course in Complex Analysis; Princeton University Press
    Zhang, Hongmei; Analyzing High-Dimensional Gene Expression and DNA Methylation Data with R; Chapman and Hall/CRC Press
    Zhang, Li-Chun; Graph Sampling;
    Zhang, Song; Design and Analysis of Pragmatic Trials; CRC Press
    Zhao, Yan-Gang.; Structural Reliability: Approaches from Perspectives of Statistical Moments; Wiley
Reviews guidelines

Reviews should be informative and express a view. While most reviews are of books, we welcome suggestions for review of any material (eg video or audio, online courses) relevant to statisticians. Please contact the reviews editor with any suggestions.

Readers want to know whether this book (or other material) could be of interest to them, or to a colleague or student. Space for reviews is limited, so every word used must earn its place. A minority of books merit a very full review, about 600–800 words; most reviews are expected to be about 300–400 words; for some books, including those little changed from a previous edition, 150 words will suffice. For Significance magazine, reviews must be no more than 250 words. Please try not to include formulae or complex mathematical expressions.

Do not hold back from offering fair and defensible (but not offensive) criticism where it is deserved. If your review exposes a book as outdated, inaccurate or unsatisfactory in other ways, you will earn the gratitude of many. Similarly, when the book has a refreshing perspective, or is particularly useful (even in a few chapters), your enthusiasm will be appreciated. Of course, you must not review material in which you have a pecuniary or similar interest.

Avoid simply quoting from the publisher’s blurb, without comment, or merely listing chapter titles, unless this is the best way to succinctly describe the content. Your review should offer more than can be found by a reader stumbling across the book in a bookshop, or advertised on a website. If the authors have offered to make publicly available a list of misprints and corrections, it will be more useful to send minor slips directly to them than to take up space in your review. But, when you find errors that are likely to mislead, then point them out!

Sometimes, two or more books on the same topic can be reviewed together; in general, comparisons of new books with the existing literature can be most helpful. We want reviews published in our journals to read well, to be authoritative, and to be useful to the statistical community. If you refer to other published work, give precise details in the conventional manner, listing such references at the end of your review.

The division between publication in Significance and Series A of the journal is now established: reviews of books aimed at the general public, undergraduate texts and historical surveys now appear in Significance, whereas more technical books, research monographs and postgraduate texts will be reviewed in Series A.

Head your review with the standard information in this order: title, author(s), publication year, edition or format, publisher, length, price and ISBN. End with your own name and your affiliation (or simply town or city where you live), and your e-mail address if you are happy for it to appear in print. Send as plain text or Word document; LaTeX markup may also be helpful if typographic features or non-English characters are relied on.

With reviews suitable for Series A, you must first contact the book reviews editor Kuldeep Kumar ( to express your interest in reviewing one of the listed books and to receive a copy for review. The editor will then arrange for you to be invited to submit your finished review to the ScholarOne system for Series A and provide you with full instructions on how to make your submission.

The book reviews editor and/or the copy editor might edit your review mildly, mainly to put it into in ‘house style’, but also to correct typographical errors etc; if an editor wishes to make any alteration of substance, he or she will run it past you first. You will, of course, also receive proofs of the text to check before publication, but the review cannot be published until you also return a signed copy of the copyright transfer agreement (CTA) that will accompany the proofs.

Last updated February 2023.