Applied Biostatistical Principles and Concepts: Clinicians’ Guide to Data Analysis and Interpretation

 Statistics  Comments Off on Applied Biostatistical Principles and Concepts: Clinicians’ Guide to Data Analysis and Interpretation
Sep 252018

The past three decades have witnessed modern advances in statistical modeling and evidence discovery in biomedical, clinical, and population-based research. With these advances come the challenges in accurate model stipulation and application of models in scientific evidence discovery

Applied Biostatistical Principles and Concepts provides practical knowledge using biological and biochemical specimen/samples in order to understand health and disease processes at cellular, clinical, and population levels. Concepts and techniques provided will help researchers design and conduct studies, then translate data from bench to clinics in attempt to improve the health of patients and populations.

This book is suitable for both clinicians and health or biological sciences students. It presents the reality in statistical modelling of health research data in a concise manner that will address the issue of “big data” type I error tolerance and probability value, effect size and confidence interval for precision, effect measure modification and interaction as well as confounders, thus allowing for more valid inferences and yielding results that are more reliable, valid and accurate.



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 Posted by at 7:32 pm

Medical Statistics: An A-Z Companion, Second Edition

 Statistics  Comments Off on Medical Statistics: An A-Z Companion, Second Edition
Sep 242018

This invaluable, jargon-free guide to essential medical terminology in an accessible A-Z format is ideal for medical, allied health and biomedical science students and researchers, clinicians and health care practitioners. Avoiding the complex language that is so often a feature of statistics and research methodology, this text provides clear and succinct explanations, clarifying meaning and showing the interdependencies between important concepts. This edition includes enhanced explanations of statistical concepts and methods―including more illustrative content―for greater accessibility. The book makes frequent use of examples from the medical literature, with reference to landmark studies, ensuring clinical relevance. It remains an ideal aid to accompany the reading and critical appraisal of medical and health care literature, now widely recognized to be a practical lifelong skill required by all health professionals throughout undergraduate and postgraduate studies and during clinical practice.
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Statistical Methods in Psychiatry and Related Fields: Longitudinal, Clustered, and Other Repeated Measures Data

 Statistics  Comments Off on Statistical Methods in Psychiatry and Related Fields: Longitudinal, Clustered, and Other Repeated Measures Data
Sep 212018

Data collected in psychiatry and related fields are complex because outcomes are rarely directly observed, there are multiple correlated repeated measures within individuals, there is natural heterogeneity in treatment responses and in other characteristics in the populations. Simple statistical methods do not work well with such data. More advanced statistical methods capture the data complexity better, but are difficult to apply appropriately and correctly by investigators who do not have advanced training in statistics. This book presents, at a non-technical level, several approaches for the analysis of correlated data: mixed models for continuous and categorical outcomes, nonparametric methods for repeated measures and growth mixture models for heterogeneous trajectories over time. Separate chapters are devoted to techniques for multiple comparison correction, analysis in the presence of missing data, adjustment for covariates, assessment of mediator and moderator effects, study design and sample size considerations. The focus is on the assumptions of each method, applicability and interpretation rather than on technical details. The intended audience are applied researchers with minimal knowledge of statistics, although the book could also benefit collaborating statisticians. The book, together with the online materials, is a valuable resource aimed at promoting the use of appropriate statistical methods for the analysis of repeated measures data.
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Modern Bayesian Statistics in Clinical Research

 Statistics  Comments Off on Modern Bayesian Statistics in Clinical Research
Sep 182018

The current textbook has been written as a help to medical / health professionals and students for the study of modern Bayesian statistics, where posterior and prior odds have been replaced with posterior and prior likelihood distributions. Why may likelihood distributions better than normal distributions estimate uncertainties of statistical test results? Nobody knows for sure, and the use of likelihood distributions instead of normal distributions for the purpose has only just begun, but already everybody is trying and using them. SPSS statistical software version 25 (2017) has started to provide a combined module entitled Bayesian Statistics including almost all of the modern Bayesian tests (Bayesian t-tests, analysis of variance (anova), linear regression, crosstabs etc.).



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Statistical Methods for Survival Trial Design: With Applications to Cancer Clinical Trials Using R

 Oncology, Statistics  Comments Off on Statistical Methods for Survival Trial Design: With Applications to Cancer Clinical Trials Using R
Sep 152018

Statistical Methods for Survival Trial Design: With Applications to Cancer Clinical Trials Using R provides a thorough presentation of the principles of designing and monitoring cancer clinical trials in which time-to-event is the primary endpoint. Traditional cancer trial designs with time-to-event endpoints are often limited to the exponential model or proportional hazards model. In practice, however, those model assumptions may not be satisfied for long-term survival trials.

This book is the first to cover comprehensively the many newly developed methodologies for survival trial design, including trial design under the Weibull survival models; extensions of the sample size calculations under the proportional hazard models; and trial design under mixture cure models, complex survival models, Cox regression models, and competing-risk models. A general sequential procedure based on the sequential conditional probability ratio test is also implemented for survival trial monitoring. All methodologies are presented with sufficient detail for interested researchers or graduate students.



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Statistics and experimental design for toxicologists

 Statistics, Toxicology  Comments Off on Statistics and experimental design for toxicologists
Sep 132018

Statistics and Experimental Design for Toxicologists has been designed as both a sourcebook for the practicing toxicologist and a textbook for the student toxicologist. Its function is to provide both with tools for the rigorous and critical analysis of experimental data. Assuming only basic mathematical skills, the volume provides a complete and exhaustive introduction to the statistical methods available to and used in the discipline. For each technique presented, a practical example is provided and a collection of problems is also included, together with appendices containing the necessary tables of test values.


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 Posted by at 2:42 pm

The Statistical Analysis of Functional MRI Data

 Statistics  Comments Off on The Statistical Analysis of Functional MRI Data
Jun 052018

The study of brain function is one of the most fascinating pursuits of m- ern science. Functional neuroimaging is an important component of much of the current research in cognitive, clinical, and social psychology. The exci- ment of studying the brain is recognized in both the popular press and the scienti?c community. In the pages of mainstream publications, including The New York Times and Wired, readers can learn about cutting-edge research into topics such as understanding how customers react to products and – vertisements (“If your brain has a ‘buy button,’ what pushes it?”, The New York Times,October19,2004),howviewersrespondtocampaignads(“Using M. R. I. ’s to see politics on the brain,” The New York Times, April 20, 2004; “This is your brain on Hillary: Political neuroscience hits new low,” Wired, November 12,2007),howmen and womenreactto sexualstimulation (“Brain scans arouse researchers,”Wired, April 19, 2004), distinguishing lies from the truth (“Duped,” The New Yorker, July 2, 2007; “Woman convicted of child abuse hopes fMRI can prove her innocence,” Wired, November 5, 2007), and even what separates “cool” people from “nerds” (“If you secretly like Michael Bolton, we’ll know,” Wired, October 2004). Reports on pathologies such as autism, in which neuroimaging plays a large role, are also common (for – stance, a Time magazine cover story from May 6, 2002, entitled “Inside the world of autism”).


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 Posted by at 6:16 pm

Statistical Methods in Epidemiologic Research

 Miscellaneous, Statistics  Comments Off on Statistical Methods in Epidemiologic Research
May 192018

With the many advances in the control of infectious disease over the last 100 years, the role of epidemiology in public health has transformed significantly. Epidemiologic research now includes the study of acute and chronic diseases, as well as the events, behaviors, and conditions associated with health.

From seasoned author Ray Merrill, this text explores how epidemiologic methods are conducted and interpreted. In four sections, Statistical Methods in Epidemiologic Research covers basic concepts in epidemiology and statistics, study designs, statistical techniques and applications, as well as special topics.

Key Features:

• Includes sections on how specific epidemiologic methods have resulted in findings that have influenced health policy and public health
• Offers optional sections involving more advanced methods
• At the end of each chapter, an applications section gives the student a clear picture of how epidemiologic methods are applied in real-world situations
• Special emphasis is given to interpreting results
• SAS code is presented in an appendix that corresponds to assessing selected methods.



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 Posted by at 6:29 pm

Biostatistics by Example Using SAS Studio

 Statistics  Comments Off on Biostatistics by Example Using SAS Studio
May 102018

Learn how to solve basic statistical problems with Ron Cody’s easy-to-follow style using the point-and-click SAS Studio tasks.

Aimed specifically at the health sciences, Biostatistics by Example Using SAS Studio, provides an introduction to SAS Studio tasks. The book includes many biological and health-related problem sets and is fully compatible with SAS University Edition.

After reading this book you will be able to understand temporary and permanent SAS data sets, and you will learn how to create them from various data sources. You will also be able to use SAS Studio statistics tasks to generate descriptive statistics for continuous and categorical data.

The inferential statistics portion of the book covers the following topics:

– paired and unpaired t tests
– one-way analysis of variance
– N-way ANOVA
– correlation
– simple and multiple regression
– logistic regression
– categorical data analysis
– power and sample size calculations

Besides describing each of these statistical tests, the book also discusses the assumptions that need to be met before running and interpreting these tests. For two-sample tests and N-way tests, nonparametric tests are also described.

This book leads you step-by-step through each of the statistical tests with numerous screen shots, and you will see how to read and interpret all of the output generated by these tests.

Experience with some basic statistical tests used to analyze medical data or classroom experience in biostatistics or statistics is required. Although the examples are related to the medical and biology fields, researchers in other fields such as psychology or education will find this book helpful. No programming experience is required.



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 Posted by at 3:07 pm

A Practical Approach to Using Statistics in Health Research: From Planning to Reporting

 Statistics  Comments Off on A Practical Approach to Using Statistics in Health Research: From Planning to Reporting
May 022018

A hands–on guide to using statistics in health research, from planning, through analysis, and on to reporting

A Practical Approach to Using Statistics in Health Research offers an easy to use, step–by–step guide for using statistics in health research. The authors use their experience of statistics and health research to explain how statistics fit in to all stages of the research process. They explain how to determine necessary sample sizes, interpret whether there are statistically significant difference in outcomes between groups, and use measured effect sizes to decide whether any changes are large enough to be relevant to professional practice.

The text walks you through how to identify the main outcome measure for your study and the factor which you think may influence that outcome and then determine what type of data will be used to record both of these. It then describes how this information is used to select the most appropriate methods to report and analyze your data. A step–by–step guide on how to use a range of common statistical procedures are then presented in separate chapters. To help you make sure that you are using statistics robustly, the authors also explore topics such as multiple testing and how to check whether measured data follows a normal distribution. Videos showing how to use computer packages to carry out all the various methods mentioned in the book are available on our companion web site. This book:

Covers statistical aspects of all the stages of health research from planning to final reporting

Explains how to report statistical planning, how analyses were performed, and the results and conclusion

Puts the spotlight on consideration of clinical significance and not just statistical significance

Explains the importance of reporting 95% confidence intervals for effect size

Includes a systematic guide for selection of statistical tests and uses example data sets and videos to help you understand exactly how to use statistics

Written as an introductory guide to statistics for healthcare professionals, students and lecturers in the fields of pharmacy, nursing, medicine, dentistry, physiotherapy, and occupational therapy, A Practical Approach to Using Statistics in Health Research:From Planning to Reporting is a handy reference that focuses on the application of statistical methods within the health research context.



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 Posted by at 1:06 pm