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Applied Medical Statistics
Jingmei Jiang (Author)
9781119716709, Wiley
Hardback, published 29 April 2022
640 pages
25.4 x 17.8 x 3.2 cm, 1.222 kg
APPLIED MEDICAL STATISTICS An up-to-date exploration of foundational concepts in statistics and probability for medical students and researchers Medical journals and researchers are increasingly recognizing the need for improved statistical rigor in medical science. In Applied Medical Statistics, renowned statistician and researcher Dr. Jingmei Jiang delivers a clear, coherent, and accessible introduction to basic statistical concepts, ideal for medical students and medical research practitioners. The book will help readers master foundational concepts in statistical analysis and assist in the development of a critical understanding of the basic rationale of statistical analysis techniques. The distinguished author presents information without assuming the reader has a background in specialized mathematics, statistics, or probability. All of the described methods are illustrated with up-to-date examples based on real-world medical research, supplemented by exercises and case discussions to help solidify the concepts and give readers an opportunity to critically evaluate different research scenarios. Readers will also benefit from the inclusion of: Perfect for postgraduate medical students, clinicians, and medical and biomedical researchers, Applied Medical Statistics will also earn a place on the shelf of any researcher with an interest in biostatistics or applying statistical methods to their own field of research.
Preface xiii Acknowledgments xv About the Companion Website xvii 1 What is Biostatistics 1 1.1 Overview 1 1.2 Some Statistical Terminology 2 1.3 Workflow of Applied Statistics 6 1.4 Statistics and Its Related Disciplines 6 1.5 Statistical Thinking 7 1.6 Summary 7 1.7 Exercises 8 2 Descriptive Statistics 11 2.1 Frequency Tables and Graphs 12 2.2 Descriptive Statistics of Numerical Data 17 2.3 Descriptive Statistics of Categorical Data 31 2.4 Constructing Statistical Tables and Graphs 38 2.5 Summary 47 2.6 Exercises 48 3 Fundamentals of Probability 53 3.1 Sample Space and Random Events 54 3.2 Relative Frequency and Probability 58 3.3 Conditional Probability and Independence of Events 60 3.4 Multiplication Law of Probability 61 3.5 Addition Law of Probability 62 3.6 Total Probability Formula and Bayes’ Rule 63 3.7 Summary 65 3.8 Exercises 65 4 Discrete Random Variable 69 4.1 Concept of the Random Variable 69 4.2 Probability Distribution of the Discrete Random Variable 70 4.3 Numerical Characteristics 73 4.4 Commonly Used Discrete Probability Distributions 75 4.5 Summary 87 4.6 Exercises 87 5 Continuous Random Variable 91 5.1 Concept of Continuous Random Variable 92 5.2 Numerical Characteristics 93 5.3 Normal Distribution 94 5.4 Application of the Normal Distribution 102 5.5 Summary 109 5.6 Exercises 110 6 Sampling Distribution and Parameter Estimation 113 6.1 Samples and Statistics 114 6.2 Sampling Distribution of a Statistic 114 6.3 Estimation of One Population Parameter 124 6.4 Estimation of Two Population Parameters 132 6.5 Summary 141 6.6 Exercises 141 7 Hypothesis Testing for One Parameter 145 7.1 Overview 145 7.2 Hypothesis Testing for One Parameter 155 7.3 Further Considerations on Hypothesis Testing 164 7.4 Summary 165 7.5 Exercises 166 8 Hypothesis Testing for Two Population Parameters 169 8.1 Testing the Difference Between Two Population Means: Paired Samples 170 8.2 Testing the Difference Between Two Population Means: Independent Samples 173 8.3 Testing the Difference Between Two Population Rates (Normal Approximation Method) 185 8.4 Summary 188 8.5 Exercises 189 9 One-way Analysis of Variance 193 9.1 Overview 193 9.3 Multiple Comparisons of Means 204 9.4 Checking ANOVA Assumptions 211 9.5 Data Transformations 217 9.6 Summary 218 9.7 Exercises 218 10 Analysis of Variance in Different Experimental Designs 221 10.1 ANOVA for Randomized Block Design 221 10.2 ANOVA for Two-factor Factorial Design 229 10.3 ANOVA for Repeated Measures Design 240 10.4 ANOVA for 2 × 2 Crossover Design 251 10.5 Summary 256 10.6 Exercises 257 11 χ2 Test 261 11.1 Contingency Table 262 11.2 χ2Test for a 2 × 2 Contingency Table 266 11.3 χ2 Test for R × C Contingency Tables 276 11.4 χ2 Goodness-of-Fit Test 280 11.5 Summary 284 11.6 Exercises 285 12 Nonparametric Tests Based on Rank 289 12.1 Concept of Order Statistics 289 12.2 Wilcoxon’s Signed-Rank Test for Paired Samples 290 12.3 Wilcoxon’s Rank-Sum Test for Two Independent Samples 295 12.4 Kruskal-Wallis Test for Multiple Independent Samples 299 12.5 Friedman’s Test for Randomized Block Design 303 12.6 Further Considerations About Nonparametric Tests 306 12.7 Summary 306 12.8 Exercises 306 13 Simple Linear Regression 311 13.1 Concept of Simple Linear Regression 311 13.2 Establishment of Regression Model 314 13.3 Application of Regression Model 321 13.4 Evaluation of Model Fitting 325 13.5 Summary 327 13.6 Exercises 328 14 Simple Linear Correlation 331 14.1 Concept of Simple Linear Correlation 331 14.2 Hypothesis Testing of Correlation Coefficient 336 14.3 Confidence Interval Estimation for Correlation Coefficient 338 14.4 Spearman’s Rank Correlation 340 14.5 Summary 342 14.6 Exercises 343 15 Multiple Linear Regression 345 15.1 Multiple Linear Regression Model 346 15.2 Hypothesis Testing 352 15.3 Evaluation of Model Fitting 356 15.4 Other Aspects of Regression 359 15.5 Summary 364 15.6 Exercises 364 16 Logistic Regression 369 16.1 Logistic Regression Model 370 16.2 Conditional Logistic Regression Model 388 16.3 Additional Remarks 394 16.4 Summary 395 16.5 Exercises 396 17 Survival Analysis 399 17.1 Overview 400 17.2 Description of the Survival Process 405 17.3 Comparison of Survival Processes 410 17.4 Cox’s Proportional Hazards Model 414 17.5 Other Aspects of Cox’s Proportional Hazard Model 421 17.6 Summary 422 17.7 Exercises 423 18 Evaluation of Diagnostic Tests 431 18.1 Basic Characteristics of Diagnostic Tests 431 18.2 Agreement Between Diagnostic Tests 443 18.3 Receiver Operating Characteristic Curve Analysis 448 18.4 Summary 456 18.5 Exercises 457 19 Observational Study Design 461 19.1 Cross-Sectional Studies 462 19.2 Cohort Studies 469 19.3 Case-Control Studies 472 19.4 Summary 474 19.5 Exercises 475 20 Experimental Study Design 477 20.1 Overview 478 20.2 Completely Randomized Design 483 20.3 Randomized Block Design 486 20.4 Factorial Design 489 20.5 Crossover Design 491 20.6 Summary 493 20.7 Exercises 493 Appendix 495 References 549 Index 557
9.2 Procedures of ANOVA 196
Subject Areas: Mathematics [PB]
