Master the essentials of data analysis in the medical field with our comprehensive selection of Biostatistics books at Jinnah Medical Bookshop—your leading online source for medical literature in Pakistan. Our collection includes the latest and most relevant textbooks designed for medical students, researchers, and professionals seeking to enhance their statistical skills. Enjoy the convenience of cash on delivery available across Pakistan, ensuring that the best resources arrive right at your doorstep. Equip yourself with the knowledge to analyze and interpret data effectively, and elevate your understanding of Biostatistics today!

 

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    SEQs and MCQs Solved Past Papers Biostatistics and Research Method and EBP

    Original price was: 565 ₨.Current price is: 450 ₨.
    SEQs and MCQs Solved Past Papers Biostatistics and Research Method and EBPFor DPT, SLP, and Pharma D StudentsUHS. KEMU. BZU. PU and All Universities of PakistanExam Master SeriesBy Muhammad Ibrahim  
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    SEQs and MCQs Solved Past Papers Biostatistics and Research Method

    Original price was: 565 ₨.Current price is: 450 ₨.
    SEQs and MCQs Solved Past Papers Biostatistics and Research MethodFor Allied Health Sciences StudentsUHS. KEMU. BZU. PU and All Universities of PakistanExam Master SeriesBy Muhammad Ibrahim 
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    Research Methodology and Basic Biostatistics by Saira Afzal 2nd Edition

    Original price was: 695 ₨.Current price is: 600 ₨.
    Research Methodology and Basic Biostatistics Saira Afzal & Mustehsan BashirISBN-10: 9696370830 ISBN-13: 978-9696370833Research methodology and Basic Biostatistics comprehensively describes the intricacies of research and biostatistics for both undergraduate and postgraduate students.
  • QR I & QR II QUANTITATIVE REASONING & BIOSTATISTICS For Medical, AHS and Nursing Students

    By Muhammad Ibrahim

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    Introduction to Biostatistics and Research Methods 2nd Edition

    Original price was: 595 ₨.Current price is: 500 ₨.
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    High-Yield Biostatistics, Epidemiology, and Public Health – Edition 4

    Original price was: 300 ₨.Current price is: 250 ₨.
    High-Yield Biostatistics, Epidemiology, and Public Health (High-Yield Series) - Fourth Edition Anthony N. Glaser MD Ph.D (Author)ISBN-13: 978-1451130171 ISBN-10: 1451130171High-Yield™ Biostatistics, Epidemiology, and Public Health, Fourth Edition provides a concise review of the biostatistics concepts that are tested in the USMLE Step 1. Information is presented in an easy-to-follow format, with High-Yield Points that help students focus on the most important USMLE Step 1 facts. The High-Yield™ outline format, with tables, diagrams, photographs, and images to clarify important material, provides a concentrated, efficient review for both course exams and the USMLE.
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    Using R for Biostatistics 1st ed.

    1,450 3,300 
    This book introduces the open source R software language that can be implemented in biostatistics for data organization, statistical analysis, and graphical presentation. In the years since the authors’ 2014 work Introduction to Data Analysis and Graphical Presentation in Biostatistics with R, the R user community has grown exponentially and the R language has increased in maturity and functionality. This updated volume expands upon skill-sets useful for students and practitioners in the biological sciences by describing how to work with data in an efficient manner, how to engage in meaningful statistical analyses from multiple perspectives, and how to generate high-quality graphics for professional publication of their research.A common theme for research in the diverse biological sciences is that decision-making depends on the empirical use of data. Beginning with a focus on data from a parametric perspective, the authors address topics such as Student t-Tests for independent samples and matched pairs; oneway and twoway analyses of variance; and correlation and linear regression. The authors also demonstrate the importance of a nonparametric perspective for quality assurance through chapters on the Mann-Whitney U Test, Wilcoxon Matched-Pairs Signed-Ranks test, Kruskal-Wallis H-Test for Oneway Analysis of Variance, and the Friedman Twoway Analysis of Variance.To address the element of data presentation, the book also provides an extensive review of the many graphical functions available with R. There are now perhaps more than 15,000 external packages available to the R community. The authors place special emphasis on graphics using the lattice package and the ggplot2 package, as well as less common, but equally useful, figures such as bean plots, strip charts, and violin plots.A robust package of supplementary material, as well as an introduction of the development of both R and the discipline of biostatistics, makes this ideal for novice learners as well as more experienced practitioners.  Buy online Medical books at Gangaram Jinnah Medical Books Shop for home delivery and Cash on delivery to all over Pakistan. All kind of medical books are available.
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    Structural equation modeling (SEM) is a very general and flexible multivariate technique that allows relationships among variables to be examined. The roots of SEM are in the social sciences. In writing this textbook, the authors look to make SEM accessible to a wider audience of researchers across many disciplines, addressing issues unique to health and medicine.SEM is often used in practice to model and test hypothesized causal relationships among observed and latent (unobserved) variables, including in analysis across time and groups. It can be viewed as the merging of a conceptual model, path diagram, confirmatory factor analysis, and path analysis. In this textbook the authors also discuss techniques, such as mixture modeling, that expand the capacity of SEM using a combination of both continuous and categorical latent variables.Features:
    • Basic, intermediate, and advanced SEM topics
    • Detailed applications, particularly relevant for health and medical scientists
    • Topics and examples that are pertinent to both new and experienced SEM researchers
    • Substantive issues in health and medicine in the context of SEM
    • Both methodological and applied examples
    • Numerous figures and diagrams to illustrate the examples
    As SEM experts situated among clinicians and multidisciplinary researchers in medical settings, the authors provide a broad, current, on the ground understanding of the issues faced by clinical and health services researchers and decision scientists. This book gives health and medical researchers the tools to apply SEM approaches to study complex relationships between clinical measurements, individual and community-level characteristics, and patient-reported scales.  Buy online Medical books at Gangaram Jinnah Medical Books Shop for home delivery and Cash on delivery to all over Pakistan. All kind of medical books are available.
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    Statistical Thinking in Clinical Trials combines a relatively small number of key statistical principles and several instructive clinical trials to gently guide the reader through the statistical thinking needed in clinical trials. Randomization is the cornerstone of clinical trials and randomization-based inference is the cornerstone of this book. Read this book to learn the elegance and simplicity of re-randomization tests as the basis for statistical inference (the analyze as you randomize principle) and see how re-randomization tests can save a trial that required an unplanned, mid-course design change.Other principles enable the reader to quickly and confidently check calculations without relying on computer programs. The `EZ’ principle says that a single sample size formula can be applied to a multitude of statistical tests. The `O minus E except after V’ principle provides a simple estimator of the log odds ratio that is ideally suited for stratified analysis with a binary outcome. The same principle can be used to estimate the log hazard ratio and facilitate stratified analysis in a survival setting. Learn these and other simple techniques that will make you an invaluable clinical trial statistician.  Buy online Medical books at Gangaram Jinnah Medical Books Shop for home delivery and Cash on delivery to all over Pakistan. All kind of medical books are available.
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    This book provides a concise point of reference for the most commonly used regression methods. It begins with linear and nonlinear regression for normally distributed data, logistic regression for binomially distributed data, and Poisson regression and negative-binomial regression for count data. It then progresses to these regression models that work with longitudinal and multi-level data structures. The volume is designed to guide the transition from classical to more advanced regression modeling, as well as to contribute to the rapid development of statistics and data science. With data and computing programs available to facilitate readers' learning experience, Statistical Regression Modeling promotes the applications of R in linear, nonlinear, longitudinal and multi-level regression. All included datasets, as well as the associated R program in packages nlme and lme4 for multi-level regression, are detailed in Appendix A. This book will be valuable in graduate courses on applied regression, as well as for practitioners and researchers in the fields of data science, statistical analytics, public health, and related fields.
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    A health disparity refers to a higher burden of illness, injury, disability, or mortality experienced by one group relative to others attributable to multiple factors including socioeconomic status, environmental factors, insufficient access to health care, individual risk factors, and behaviors and inequalities in education. These disparities may be due to many factors including age, income, and race. Statistical Methods in Health Disparity Research will focus on their estimation, ranging from classical approaches including the quantification of a disparity, to more formal modeling, to modern approaches involving more flexible computational approaches.Features:
    • Presents an overview of methods and applications of health disparity estimation
    • First book to synthesize research in this field in a unified statistical framework
    • Covers classical approaches, and builds to more modern computational techniques
    • Includes many worked examples and case studies using real data
    • Discusses available software for estimation
    The book is designed primarily for researchers and graduate students in biostatistics, data science, and computer science. It will also be useful to many quantitative modelers in genetics, biology, sociology, and epidemiology. 
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    Third-variable effect refers to the effect transmitted by third-variables that intervene in the relationship between an exposure and a response variable. Differentiating between the indirect effect of individual factors from multiple third-variables is a constant problem for modern researchers.Statistical Methods for Mediation, Confounding and Moderation Analysis Using R and SAS introduces general definitions of third-variable effects that are adaptable to all different types of response (categorical or continuous), exposure, or third-variables. Using this method, multiple third- variables of different types can be considered simultaneously, and the indirect effect carried by individual third-variables can be separated from the total effect. Readers of all disciplines familiar with introductory statistics will find this a valuable resource for analysis.Key Features:
    • Parametric and nonparametric method in third variable analysis
    • Multivariate and Multiple third-variable effect analysis
    • Multilevel mediation/confounding analysis
    • Third-variable effect analysis with high-dimensional data Moderation/Interaction effect analysis within the third-variable analysis
    • R packages and SAS macros to implement methods proposed in the book
     
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    This book aims to compile typical fundamental-to-advanced statistical methods to be used for health data sciences. Although the book promotes applications to health and health-related data, the models in the book can be used to analyze any kind of data. The data are analyzed with the commonly used statistical software of R/SAS (with online supplementary on SPSS/Stata). The data and computing programs will be available to facilitate readers’ learning experience. There has been considerable attention to making statistical methods and analytics available to health data science researchers and students. This book brings it all together to provide a concise point-of-reference for the most commonly used statistical methods from the fundamental level to the advanced level. We envisage this book will contribute to the rapid development in health data science. We provide straightforward explanations of the collected statistical theory and models, compilations of a variety of publicly available data, and illustrations of data analytics using commonly used statistical software of SAS/R. We will have the data and computer programs available for readers to replicate and implement the new methods. The primary readers would be applied data scientists and practitioners in any field of data science, applied statistical analysts and scientists in public health, academic researchers, and graduate students in statistics and biostatistics. The secondary readers would be R&D professionals/practitioners in industry and governmental agencies. This book can be used for both teaching and applied research. 
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    Signal Detection for Medical Scientists: Likelihood Ratio Based Test-Based Methodology presents the data mining techniques with focus on likelihood ratio test (LRT) based methods for signal detection. It emphasizes computational aspect of LRT methodology and is pertinent for first-time researchers and graduate students venturing into this interesting field.The book is written as a reference book for professionals in pharmaceutical industry, manufactures of medical devices, and regulatory agencies. The book deals with the signal detection in drug/device evaluation, which is important in the post-market evaluation of medical products, and in the pre-market signal detection during clinical trials for monitoring procedures.It should also appeal to academic researchers, and faculty members in mathematics, statistics, biostatistics, data science, pharmacology, engineering, epidemiology, and public health. Therefore, this book is well suited for both research and teaching.Key Features:
    • Includes a balanced discussion of art of data structure, issues in signal detection, statistical methods and analytics, and implementation of the methods
    • Provides a comprehensive summary of the LRT methods for signal detection including the basic theory and extensions for varying datasets that may be large post-market data or pre-market clinical trial data
    • Contains details of scientific background, statistical methods, and associated algorithms that a reader can quickly master the materials and apply methods in the book on one’s own problems
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    This edited collection commemorates the career of Dr. S. Lynne Stokes by highlighting recent advances in her areas of research interest, emphasizing practical applications and future directions. It serves as a collective effort of leading statistical scientists who work at the cutting edge in statistical sampling.S. Lynne Stokes is Professor of Statistical Science and Director of the Data Science Institute at Southern Methodist University, and Senior Fellow at the National Institute of Statistical Sciences. She has enjoyed a distinguished research career, making fundamental contributions to a variety of fields in statistical sampling. Reflecting on Professor Stokes' main areas of research, this volume is structured into three main parts:I. ranked-set sampling, judgment post-stratified sampling, and capture-recapture methodsII. nonsampling errors in statistical samplingIII. educational and behavioral statistics.This collection will be of interest to researchers, advanced students, and professionals in the public and private sectors who would like to learn more about latest advancements in statistical sampling, particularly those who work in educational and behavioral statistics. 
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    Real-world evidence is defined as evidence generated from real-world data outside randomized controlled trials. As scientific discoveries and methodologies continue to advance, real-world data and their companion technologies offer powerful new tools for evidence generation. Real-World Evidence in a Patient-Centric Digital Era provides perspectives, examples, and insights on the innovative application of real-world evidence to meet patient needs and improve healthcare, with a focus on the pharmaceutical industry.This book presents an overview of key analytical issues and best practices. Special attention is paid to the development, methodologies, and other salient features of the statistical and data science techniques that are customarily used to generate real-world evidence. It provides a review of key topics and emerging trends in cutting-edge data science and health innovation.Features:
    • Provides an overview of statistical and analytic methodologies in real-world evidence to generate insights on healthcare, with a special focus on the pharmaceutical industry
    • Examines timely topics of high relevance to industry such as bioethical considerations, regulatory standards, and compliance requirements
    • Highlights emerging and current trends, and provides guidelines for best practices
    • Illustrates methods through examples and use-case studies to demonstrate impact
    • Provides guidance on software choices and digital applications for successful analytics
    Real-World Evidence in a Patient-Centric Digital Era will be a vital reference for medical researchers, health technology innovators, data scientists, epidemiologists, population health analysts, health economists, outcomes researchers, policymakers, and analysts in the healthcare industry.
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    This book is designed to train graduate students across disciplines within the fields of public health and medicine, with the goal of guiding them in the transition to independent researchers. It focuses on theories, principles, techniques, and methods essential for data processing and quantitative analysis to address medical, health, and behavioral challenges. Students will learn to access to existing data and process their own data, quantify the distribution of a medical or health problem to inform decision making; to identify influential factors of a disease/behavioral problem; and to support health promotion and disease prevention. Concepts, principles, methods and skills are demonstrated with SAS programs, figures and tables generated from real, publicly available data. In addition to various methods for introductory analysis, the following are featured, including 4-dimensional measurement of distribution and geographic mapping, multiple linear and logistic regression, Poisson regression, Cox regression, missing data imputing, and statistical power analysis.  Buy online Medical books at Gangaram Jinnah Medical Books Shop for home delivery and Cash on delivery to all over Pakistan. All kind of medical books are available.
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    Quantitative Methodologies and Process for Safety Monitoring and Ongoing Benefit Risk Evaluation provides a comprehensive coverage on safety monitoring methodologies, covering both global trends and regional initiatives. Pharmacovigilance has traditionally focused on the handling of individual adverse event reports however recently there had been a shift towards aggregate analysis to better understand the scope of product risks.Written to be accessible not only to statisticians but also to safety scientists with a quantitative interest, this book aims to bridge the gap in knowledge between medical and statistical fields creating a truly multi-disciplinary approach that is very much needed for 21st century safety evaluation.
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    Principles of Biostatistics, Third Edition is a concepts-based introduction to statistical procedures that prepares public health, medical, and life sciences students to conduct and evaluate research. With an engaging writing style and helpful graphics, the emphasis is on concepts over formulas or rote memorization. Throughout the book, the authors use practical, interesting examples with real data to bring the material to life. Thoroughly revised and updated, this third edition includes a new chapter introducing the basic principles of Study Design, as well as new sections on sample size calculations for two-sample tests on means and proportions, the Kruskal-Wallis test, and the Cox proportional hazards model.Key Features:
    • Includes a new chapter on the basic principles of study design.
    • Additional review exercises have been added to each chapter.
    • Datasets and Stata and R code are available on the book’s website.
    The book is divided into three parts. The first five chapters deal with collections of numbers and ways in which to summarize, explore, and explain them. The next two chapters focus on probability and introduce the tools needed for the subsequent investigation of uncertainty. It is only in the eighth chapter and thereafter that the authors distinguish between populations and samples and begin to investigate the inherent variability introduced by sampling, thus progressing to inference. Postponing the slightly more difficult concepts until a solid foundation has been established makes it easier for the reader to comprehend them.  Buy online Medical books at Gangaram Jinnah Medical Books Shop for home delivery and Cash on delivery to all over Pakistan. All kind of medical books are available.
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    This book addresses the challenge of presenting biostatistics to medical and health science audiences coherently. Tailored for students and researchers, its 13 chapters progress logically from foundational concepts like measurement scales and statistical calculations to advanced topics such as probability, correlation, regression and health and disease measures. Practical examples enhance relevance, and its gradual approach ensures easy comprehension even for non-statisticians. The book's practical emphasis shines as it culminates in teaching the use of SPSS software for result interpretation, bridging theory and practice effectively. It empowers medical professionals to confidently understand and apply statistical concepts in their work, serving as an indispensable resource in navigating the intricacies of biostatistics in medical and health sciences. 
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