Introduction to biostatistical applications in health research with Microsoft Office Excel and R / Robert P. Hirsch.
By: Hirsch, Robert P [author.]
Language: English Publisher: Hoboken, NJ : John Wiley & Sons, Inc, 2021Edition: Second editionDescription: 1 online resourceContent type: text Media type: computer Carrier type: online resourceISBN: 9781119722649; 9781119722625Uniform titles: Introduction to biostatistical applications in health research with Microsoft Office Excel Subject(s): Microsoft Excel (Computer file) | Biostatistics -- methods | Mathematical Computing | Data Interpretation, Statistical | SoftwareGenre/Form: Electronic books.DDC classification: 610.285 LOC classification: R858Online resources: Full text is available at Wiley Online Library Click here to view| Item type | Current location | Home library | Call number | Status | Date due | Barcode | Item holds |
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COLLEGE LIBRARY | COLLEGE LIBRARY | 610.285 H6157 2021 (Browse shelf) | Available | CL-53149 |
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| 610.285 D3607 2022 Deep learning for targeted treatments : transformation in healthcare / | 610.285 D5696 2022 Digitization of healthcare data using blockchain / | 610.285 Em326 2018 Emerging technologies for health and medicine : virtual reality, augmented reality, artificial intelligence, internet of things, robotics, industry 4.0 / | 610.285 H6157 2021 Introduction to biostatistical applications in health research with Microsoft Office Excel and R / | 610.285 In3 2010 Information discovery on electronic health records / | 610.285 In34 2022 Information practices and knowledge in health / | 610.285 In34 2022 Information practices and knowledge in health / |
Preceded by Introduction to biostatistical applications in health research with Microsoft Office Excel / Robert P. Hirsch. 2016.
ABOUT THE AUTHOR
Robert P. Hirsch is on the faculty for the Foundation for the Advanced Education in the Sciences within the Graduate School at the National Institutes of Health. He is also a retired Professor of Epidemiology and Biostatistics and Adjunct Professor of Statistics at The George Washington University. Dr. Hirsch is the author of numerous books in the field of health research and practice.
TABLE OF CONTENTS
Preface to First Edition xiii
Preface to Second Edition xv
About the Companion Website xvii
Part One Basic Concepts 1
1 Thinking About Chance 3
1.1 Properties of Probability 4
1.2 Combinations of Event 8
1.2.1 Intersections 8
1.2.2 Unions 13
1.3 Bayes’ Theorem 16
Chapter Summary 19
Exercises 20
2 Describing Distributions 25
2.1 Types of Data 26
2.2 Describing Distributions Graphically 27
2.2.1 Graphing Discrete Data 27
2.2.2 Graphing Continuous Data 30
2.3 Describing Distributions Mathematically 36
2.3.1 Parameter of Location 37
2.3.2 Parameter of Dispersion 41
2.4 Taking Chance into Account 48
2.4.1 Standard Normal Distribution 49
Chapter Summary 59
Exercises 62
3 Examining Samples 65
3.1 Nature of Samples 66
3.2 Estimation 67
3.2.1 Point Estimates 67
3.2.2 The Sampling Distribution 73
3.2.3 Interval Estimates 78
3.3 Hypothesis Testing 82
3.3.1 Relationship Between Interval Estimation and Hypothesis Testing 89
Chapter Summary 91
Exercises 93
Part Two Univariable Analyses 97
4 Univariable Analysis of A Continuous Dependent Variable 101
4.1 Student’s t-Distribution 103
4.2 Interval Estimation 106
4.3 Hypothesis Testing 109
Chapter Summary 113
Exercises 114
5 Univariable Analysis of An Ordinal Dependent Variable 119
5.1 Nonparametric Methods 120
5.2 Estimation 123
5.3 Wilcoxon Signed-Rank Test 124
5.4 Statistical Power of Nonparametric Tests 128
Chapter Summary 128
Exercises 129
6 Univariable Analysis of A Nominal Dependent Variable 133
6.1 Distribution of Nominal Data 134
6.2 Point Estimates 135
6.2.1 Probabilities 136
6.2.2 Rates 138
6.3 Sampling Distributions 142
6.3.1 Binomial Distribution 143
6.3.2 Poisson Distribution 146
6.4 Interval Estimation 149
6.5 Hypothesis Testing 151
Chapter Summary 155
Exercises 156
Part Three Bivariable Analyses 161
7 Bivariable Analysis of A Continuous Dependent Variable 163
7.1 Continuous Independent Variable 163
7.1.1 Regression Analysis 165
7.1.2 Correlation Analysis 189
7.2 Ordinal Independent Variable 207
7.3 Nominal Independent Variable 207
7.3.1 Estimating the Difference between the Groups 208
7.3.2 Taking Chance into Account 209
Chapter Summary 218
Exercises 221
8 Bivariable Analysis of An Ordinal Dependent Variable 227
8.1 Ordinal Independent Variable 228
8.2 Nominal Independent Variable 236
Chapter Summary 241
Exercises 243
9 Bivariable Analysis of A Nominal Dependent Variable 245
9.1 Continuous Independent Variable 246
9.1.1 Estimation 247
9.1.2 Hypothesis Testing 255
9.2 Nominal Independent Variable 258
9.2.1 Dependent Variable Not Affected by Time: Unpaired Design 259
9.2.2 Hypothesis Testing 266
9.2.3 Dependent Variable Not Affected by Time: Paired Design 277
9.2.4 Dependent Variable Affected by Time 283
Chapter Summary 286
Exercises 288
Part Four Multivariable Analyses 293
10 Multivariable Analysis of A Continuous Dependent Variable 295
10.1 Continuous Independent Variables 296
10.1.1 Multiple Regression Analysis 297
10.1.2 Multiple Correlation Analysis 317
10.2 Nominal Independent Variables 319
10.2.1 Analysis of Variance 320
10.2.2 Posterior Testing 331
10.3 Both Continuous and Nominal Independent Variables 340
10.3.1 Indicator (Dummy) Variables 341
10.3.2 Interaction Variables 343
10.3.3 General Linear Model 348
Chapter Summary 355
Exercises 358
11 Multivariable Analysis of An Ordinal Dependent Variable 367
11.1 Nonparametric Anova 369
11.2 Posterior Testing 375
Chapter Summary 380
Exercises 381
12 Multivariable Analysis of A Nominal Dependent Variable 385
12.1 Continuous and/or Nominal Independent Variables 387
12.1.1 Maximum Likelihood Estimation 387
12.1.2 Logistic Regression Analysis 389
12.1.3 Cox Regression Analysis 399
12.2 Nominal Independent Variables 401
12.2.1 Stratified Analysis 402
12.2.2 Relationship Between Stratified Analysis and Logistic Regression 410
12.2.3 Life Table Analysis 414
Chapter Summary 424
Exercises 427
13 Testing Assumptions 433
13.1 Continuous Dependent Variables 436
13.1.1 Assuming A Gaussian Distribution 437
13.1.2 Transforming Dependent Variables 477
13.1.3 Assuming Equal Variances 485
13.1.4 Assuming Additive Relationships 494
13.1.5 Dealing With Outliers 506
13.2 Nominal Dependent Variables 507
13.2.1 Assuming a Gaussian Distribution 507
13.2.2 Assuming Equal Variances 510
13.2.3 Assuming Additive Relationships 511
13.3 Independent Variables 511
Chapter Summary 513
Exercises 516
Appendix A: Flowcharts 521
Appendix B: Statistical Tables 527
Appendix C: Standard Distributions 597
Appendix D: Excel Primer 601
Appendix E: R Primer 605
Appendix F: Answers To Odd Exercises 609
Index 611
"Focusing on a basic understanding of the methods and analyses in health research, Introduction to Biostatistical Applications in Health Research with Microsoft Office Excel, 2e provides statistical concepts for interpreting results using Excel. The book emphasizes the application of methods and presents the most common methodological procedures in health research, which includes multiple regression, ANOVA, ANCOVA, logistic regression, Cox regression, stratified analysis, life table analysis, and nonparametric parallels. Some updates for this new edition: The flowcharts from the first edition will be expanded to include indicators of the assumptions of each procedure. This will be added to facilitate selection of a statistical approach to analyze a particular set of data. The existing twelve chapters describing statistical principals and statistical methods will be maintained. They have been proven to provide students with a clear and useful approach to the subject in use as a textbook and workbook in a graduate statistics course. An additional chapter will be added to the book that discusses the assumptions of statistical procedures. This chapter will describe each assumption, tell how to determine if the assumption is appropriate for a particular set of data, and provide solutions to situations in which the assumptions are not me by the data set. This chapter will provide students and researchers with the information they need to select an appropriate method of analysis and to apply that method to a set of data. The workbook will include a corresponding chapter that will provide students with practice identifying assumptions, testing for their satisfaction, and applying solutions to violation of assumptions. R will also be included to broaden the appeal and audience for the book"-- Provided by publisher.
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