TY - BOOK AU - Hirsch,Robert P. TI - Introduction to biostatistical applications in health research with Microsoft Office Excel and R SN - 9781119722649 AV - R858 U1 - 610.285 23 PY - 2021/// CY - Hoboken, NJ PB - John Wiley & Sons, Inc KW - Microsoft Excel (Computer file) KW - Biostatistics KW - methods KW - Mathematical Computing KW - Data Interpretation, Statistical KW - Software KW - Electronic books N1 - 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 N2 - "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"-- UR - https://onlinelibrary.wiley.com/doi/book/10.1002/9781119722687 ER -