Biostatistics with 'R' : a guide for medical doctors / Marco Moscarelli.
This book aims not only to introduce fundamental biostatistics topics but to explain them through R-project (R-studio). 'R' is perhaps the more used statistical software in the medical field. It is structured as a 'scientific journey' and comes with a sham yet realistic dataset r...
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| Language: | English |
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MARC
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| 100 | 1 | |a Moscarelli, Marco. | |
| 245 | 1 | 0 | |a Biostatistics with 'R' : |b a guide for medical doctors / |c Marco Moscarelli. |
| 260 | |a Cham : |b Springer, |c 2023. | ||
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| 505 | 0 | |a Intro -- Foreword -- Preface -- Contents -- Chapter 1: Introduction -- 1.1 Introduction -- 1.2 What Is the Dataset About? -- 1.3 What You Will Learn -- 1.4 Why This Book? -- 1.5 How This Book Works -- 1.6 What Is "R" (and R-Studio)? -- 1.7 Who Is This Book For? -- Chapter 2: How "R" Works -- 2.1 Downloading "R" and R-Studio -- 2.2 What R-Studio Looks Like -- 2.3 Running Simple Codes in the "R"-Console -- 2.4 To Practice with a More Advanced Code -- 2.5 Getting Help in "R" -- 2.6 The Hash Symbol # -- 2.7 The Problem of Missing Data -- 2.8 Misspelling the Code | |
| 505 | 8 | |a 2.9 Setting the Working Directory -- 2.10 Working with Scripts -- 2.11 R-Packages -- 2.12 Installing R-Packages -- 2.13 Loading R-Packages -- 2.14 How Many R-Packages Do We Need? -- 2.15 Conclusions -- Further Readings -- Chapter 3: Exploratory Data Analysis in "R" -- 3.1 Software and R-Package Required for This Chapter -- 3.2 Importing a Dataset into "R" -- 3.3 Fundamental Function to Explore a Dataset -- 3.4 Subsetting -- 3.5 Subsetting with Base-R -- 3.6 More Examples of Basic Subsetting -- 3.7 The Attach Function -- 3.8 Storing a Dataset as a Tibble for Use with the tidyverse R-Package | |
| 505 | 8 | |a 3.9 Frequently Used Subsetting Functions -- 3.10 Conclusions -- Further Readings -- Chapter 4: Data Types in "R" -- 4.1 Software and R-Packages Required for This Chapter -- 4.2 Where to Find the Example Dataset and the Script for This Chapter -- 4.3 What Is the Nature of Our Data? -- 4.4 Numeric Data -- 4.5 Integer -- 4.6 Character -- 4.7 Factors -- 4.8 Variable Classification -- 4.9 Misleading Data Encoding -- 4.10 Different Types of Variables Need Different Types of Statistical Analysis -- 4.11 Data Transformation and the Benefit of Continuous Variables -- 4.12 Missing Values | |
| 505 | 8 | |a 4.13 The CreateTableOne Function -- 4.14 Conclusion -- Further Readings -- Chapter 5: Data Distribution -- 5.1 Software and R-Packages Required for This Chapter -- 5.2 Where to Download the Example Dataset and the Script for This Chapter -- 5.3 Normality Testing -- 5.4 Histogram -- 5.5 Normality Testing -- 5.6 More About Visual Inspection with Regard to Normality -- 5.7 Do We Need to Test for Normality in All Cases? -- 5.8 Central Limit Theory -- 5.9 Properties of Normal Distribution -- 5.10 Subsetting for Normality Testing -- 5.11 Hint from the Grammar of Graphic -- 5.12 Boxplot | |
| 505 | 8 | |a 5.13 How to Treat Non-numeric Variables -- 5.14 Plotting Categorical Variables -- 5.15 Conclusion -- Further Readings -- Chapter 6: Precision, Accuracy and Indices of Central Tendency -- 6.1 Software and R-Packages Required for This Chapter -- 6.2 Where to Download the Example Dataset and the Script for This Chapter -- 6.3 Precision -- 6.4 The Relation Between Sample Size and Precision -- 6.5 Variance and Standard Deviation -- 6.6 Population and Sample Variance -- 6.7 Standard Error of the Mean vs Standard Deviation -- 6.8 Accuracy and Confidence Intervals -- 6.9 Mean, Median, Mode | |
| 520 | |a This book aims not only to introduce fundamental biostatistics topics but to explain them through R-project (R-studio). 'R' is perhaps the more used statistical software in the medical field. It is structured as a 'scientific journey' and comes with a sham yet realistic dataset ready to be analysed. The dataset along with the R-script can be downloaded from GitHub, and each chapter has dedicated scripts that will enhance the understanding of R and biostatistics. Specifically designed for whoever works in the medical-academic environment, this practical guide will help the reader to become familiar with basic to advanced biostatistics topic (descriptive - analysis / regression etc.) and to gain solid knowledge of R. . | ||
| 504 | |a Includes bibliographical references. | ||
| 588 | 0 | |a Online resource; title from PDF title page (SpringerLink, viewed August 28, 2023). | |
| 650 | 0 | |a Biometry |x Data processing. | |
| 650 | 0 | |a R (Computer program language) | |
| 776 | 0 | 8 | |c Original |z 3031330722 |z 9783031330728 |w (OCoLC)1375991571 |
| 856 | 4 | 0 | |u https://colorado.idm.oclc.org/login?url=https://link.springer.com/10.1007/978-3-031-33073-5 |z Full Text (via Springer) |
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| 956 | |a Springer e-books | ||
| 956 | |b Springer Nature - Springer Medicine eBooks 2023 English International | ||
| 998 | |b Added to collection springerlink.ebooksmedicine2023 | ||
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