Optimal Data Analysis, LLC (ODA), is a statistical consulting company specializing in design, measurement and analysis aspects of all maximum-accuracy methods. We provide theoretical and applied research involving optimal statistical methods in one location—serving as both nursery and proving-ground for cutting-edge science. ODA provides a free eJournal, Optimal Data Analysis (ODA), for which there is no subscription or publication fee. The journal is provided so that all may acquire leading-edge ideas, findings, experiments, and reviews in this field. Anyone with access to the internet has access to the journal without charge, and anyone who writes an article concerning maximum-accuracy methods may publish in the journal without charge. ODA offers an assortment of statistical software, consulting and educational services and products, as well as “software as service” and special-purpose integrated systems. A blog is the newest addition to the ODA information network, and is designed to keep the community of people interested in maximizing accuracy abreast of new success stories and opportunities.
Instant, global access to the world’s accumulated knowledge, the latest reports, the most current software, and state-of-the-art computing infrastructure—all accessible through a smart phone…
Staff scientists as well as affiliated consultants are available on a contractual consulting basis to assist in study design (hypothesis generation, measure and metric design, statistical power analysis, statistical analysis plan), statistical analysis (together our staff and associates are experts in most traditional methods, and we have developed and published more than 70 new exact statistical procedures), report generation (together amassing more than 2,000 peer-reviewed journal articles and 25 books), grant and contract proposal preparation (together receiving more than $40 million in research funding, our services offered include study design, hypothesis generation, measure and metric design, statistical power analysis, statistical analysis plan, statistical analysis, and report generation and dissemination), and custom integrated systems (ODA scientists and engineers have an impressive pedigree in creating a wide variety of industrial and commercial integrated systems, extending more than three decades). ODA also offers a variety of on-site or off-site custom educational services, including colloquia (1-2 hours), and interactive lectures (2-8 hours) and workshops (1-2 days).
Open Access (Free)
Access to and publication in Optimal Data Analysis (ODA) is free.
ODA is a multidisciplinary journal specializing in maximum-accuracy methods. All quantitative areas of inquiry are eligible for publication in ODA, and are welcomed. Infusion of new hypothesis and data configurations are often the source of new discoveries.
ODA is intended to focus the world’s theoretical and applied research involving optimal statistical methods in one location, to provide both nursery and proving-ground for cutting-edge science, for all to learn and collaborate and prosper intellectually. ODA has, and seeks additional international academic ambassadors who cross-transliterate articles published in ODA, and in collaborating journals publishing in languages other than English, in order to facilitate a world-wide academic community.
ODA is designed to provide real-time publishing, to provide the most current progress to the world audience with minimal delay.
ODA is designed to be free for all, to put all scientists at the cusp of the leading-edge ideas, findings, experiments, and reviews. Any scientist with access to the internet has access to ODA without charge. Any scientist who writes a world-class article concerning maximum-accuracy methods may publish in ODA without charge.
ODA is pleased to provide rapid, constructive reviews from world-class technical and applied experts. As manuscripts representing new areas of inquiry are submitted, additional substantive experts will be added to the Board of Editors. In addition, authors of all manuscripts submitted to ODA are required to provide a roster of qualified (and disqualified) reviewers for their work.
ODA is designed to be flexible, capable of growing in real-time to meet the needs of the scientific community. As new areas of inquiry are discovered they will be presented as a subsection of the Table of Contents. In the future, if a sufficient number of submissions within a given substantive discipline (e.g., psychology, education, finance, medicine, biology, space science) or subspecialty (e.g., clinical psychology, emergency medicine, molecular biology) begins to occur reliably, ODA will be expanded to include additional series.
ODA is working to provide a forum to allow real-time, world-wide discussion regarding all topics of relevance to the journal, and to provide international networking among scientists who speak a common language—maximum-accuracy methodology.
ODA caters to the widest possible audience—students and scientists in all quantitative areas of inquiry. Accordingly, manuscripts are sought representing all academic societies, many of which have their own formatting styles and manuscript preparation instructions. A particularly thorough author and article preparation set is offered by the Journal of the American Medical Society (http://jama.ama-assn.org/misc/ifora.dtl), and is recommended reading for all students and scientists.
Authors who wish to publish a manuscript in ODA should write keeping in mind the breadth of the audience’s background. Articles should “blend” with others published in ODA in style and appearance, to the extent possible (copy editors may offer suggestions in this area). Examine ODA articles similar in structure to the article you are preparing, and adopt a similar format.
Criteria for publication are standard: all authors on the paper must have contributed (the project described would not have been possible without each author’s contribution), all of the major contributors must be authors, and the manuscript must pass editorial review. Prospective authors are encouraged to recommend any specific reviewer(s) with substantive expertise in the area of the submitted paper.
With respect to reference citations in the body of the manuscript, use numbers (see ODA for examples). With respect to reference citations at the end of the manuscript, adopt the style of the academic society of which you are a member (or in whose journals you publish), or the style of any other academic society of your choice. Hybrids are acceptable: essential information includes authors (list the first five authors, then use “et al.”), article, journal, year, volume, and pages. For books, list authors, title, year of publication, and publisher. Refer to articles in ODA for examples of reference citations.
Manuscripts MUST be submitted in Windows Word® 93 or later. Format submitted manuscripts to appear as an article in ODA. If authors are unable to produce such a manuscript, consulting word processing technicians are available at ODA at an hourly rate. Permission to publish from all named authors is required for all accepted manuscripts prior to release.
Financial relationships (such as employment, consultancies, stock ownership, honoraria, paid expert testimony) are the most easily identifiable conflicts of interest and the most likely to undermine the credibility of the journal, the authors, and of science itself. However, conflicts can occur for other reasons, such as personal relationships, academic competition, and intellectual passion. All potential (co)authors must disclose any potential conflicts of interest, and only articles having (co)authors without any potential conflicts of interest will be published in Optimal Data Analysis.
Patients have a right to privacy that should not be infringed without informed consent. Identifying information, including patients’ names, initials, or hospital numbers, should not be published in written descriptions, photographs, and pedigrees unless the information is essential for scientific purposes and the patient (or parent or guardian) gives written informed consent for publication. Informed consent for this purpose requires that a patient who is identifiable be shown the manuscript to be published. Authors should identify Individuals who provide writing assistance and disclose the funding source for this assistance.
Identifying details should be omitted if they are not essential. Complete anonymity is difficult to achieve, however, and informed consent should be obtained if there is any doubt. For example, masking the eye region in photographs of patients is inadequate protection of anonymity. If identifying characteristics are altered to protect anonymity, such as in genetic pedigrees, authors should provide assurance that alterations do not distort scientific meaning and editors should so note. Only those articles for which these criteria have been satisfied will be published in Optimal Data Analysis.
Human and Animal Rights
When reporting experiments on human subjects, authors should indicate whether the procedures followed were in accordance with the ethical standards of the responsible committee on human experimentation (institutional and national) and with the Helsinki Declaration of 1975, as revised in 2000 (5). If doubt exists whether the research was conducted in accordance with the Helsinki Declaration, the authors must explain the rationale for their approach, and demonstrate that the institutional review body explicitly approved the doubtful aspects of the study. When reporting experiments on animals, authors should be asked to indicate whether the institutional and national guide for the care and use of laboratory animals was followed. Only those articles for which these criteria have been satisfied will be published in Optimal Data Analysis.
ODA Editorial Board
Fred B. Bryant, Ph.D., Co-Editor
Professor, Department of Psychology, Loyola University Chicago, Chicago, IL. Dr. Fred B. Bryant received his Ph.D. in social psychology from Northwestern University in 1980. He received a National Research Service Award from the National Institute of Mental Health for postdoctoral training in survey research at the University of Michigan’s Institute for Social Research (1979-82). In 1982, he joined the faculty at Loyola University Chicago as an Assistant Professor of Psychology, and was promoted to full professor in 1990. He teaches undergraduate and graduate classes in social psychology, research methods, advanced statistics, and structural equation modeling. He was faculty member of the year at Loyola University Chicago in 2005. Dr. Bryant has roughly 200 professional publications in personality, social psychology, behavioral medicine, and psychometrics. He has helped secure more than $16 million in research grants. He is on the editorial board of the Journal of Personality Assessment and Basic and Applied Social Psychology. Dr. Bryant is perhaps best known for his work on “savoring,” or cognitive and behavioral processes underlying positive emotions. He has extensive consulting experience in applied settings including medicine, education, marketing, and program evaluation, and he has served as an expert witness in several federal court cases involving theory, methodology, and statistics in social and industrial-organizational psychology. Dr. Bryant has been using optimal data analysis to analyze research data since 1993.
Robert C. Soltysik, M.S., Co-Editor
Independent Consultant. Robert Soltysik received his M.S. in industrial and systems engineering from the University of Illinois at Chicago in 1983. He is currently developing statistical systems in collaboration and equal partnership with Paul Yarnold at Optimal Data Analysis, LLC. He has consulted for many national and global companies in the fields of operations research and statistics, including the development of a press sequencing optimization system for magazine manufacturing, a personnel-selection system for a national drugstore chain, and interactive internet-based clinical intervention systems. He is the co-discoverer of the ODA paradigm, has created numerous ODA software systems, and has authored nearly four dozen articles concerning theoretical and/or applied aspects of ODA. Robert Soltysik and Paul Yarnold co-discovered the ODA paradigm, founded Optimal Data Analysis, and created a suite of software systems including UniODA™, MegaODA™, and CTA™.
Paul R. Yarnold, Ph.D., Editor
President, Optimal Data Analysis, LLC. Dr. Yarnold received his Ph.D. in academic social psychology from the University of Illinois at Chicago in 1984. He joined the faculty of Northwestern University Medical School (NUMS) as an Assistant Professor of Internal Medicine in 1985, and simultaneously as Adjunct Assistant Professor of Psychology at the University of Illinois at Chicago (UIC). In 1991 he was promoted to Research Professor of Internal Medicine at NUMS, and Adjunct Professor of Psychology at UIC. In 2000 he changed primary affiliation to the Division of Emergency Medicine, and was instrumental in its ontogenesis into the Department of Emergency Medicine. During his tenure at NUMS he conducted research within Divisions including Rehabilitation, Cardiology, Cancer, Hematology/Oncology, Plastic Surgery, OB/GYN, Allergy/Immunology, Internal, Pediatric, Geriatric, Psychiatry, Hospital, Emergency, and Behavioral Medicine, and Health Psychology, and conducted a full-time research and development program in theoretical statistics. He published more than 300 peer-reviewed journal articles primarily in the fields of medicine, statistics, and psychology, five books, six software systems, earned more than $15 million in research funding, won several patents, served on four journal editorial boards and as Ad Hoc reviewer for sixty journals, and was elected Fellow of the Society of Behavioral Medicine, and of the American Psychological Association, in Divisions 5 (Evaluation, Measurement and Statistics) and 38 (Health Psychology). In 2010, Paul left Northwestern University and the University of Illinois at Chicago to become an entrepreneurial scientist, and now focuses on furthering the development of the ODA paradigm. Paul Yarnold and Robert Soltysik co-discovered the ODA paradigm, founded Optimal Data Analysis, and created a suite of software systems including UniODA™, MegaODA™, and CTA™.
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