Textbook of Medical Statistics : For Medical Students

This book introduces basic concepts, principle, and methods of medical statistics systematically and practically, especially in the statistical design of the experiment in terms of the specific problems, adequate use of statistical methods based on actual data and the reasonable explanation for statistical results. This textbook combines statistical methods with the common application of SPSS software, which is flexible, convenient, and user-friendly; thus, students can focus on the deep understanding of statistics. The authors emphasize the application and generalization of statistical methods, and combine these methods with the modern statistical theory, such as sequential contingency table and multivariate statistical modelling, etc. This book is a useful textbook for graduate and undergraduate students in medical schools, including MBBS (Bachelor of Medicine and Bachelor of Surgery) student. Contents Chapter 1: Introduction to Medical Statistics 1.1 The Definition of Medical Statistics 1.2 Variables and Types of Data 1.3 Probabilities 1.4 Populations and Samples 1.5 Steps of Statistical Work Chapter 2: Study Design, Sample Size Estimation, and Selection of Statistical Method 2.1 Introduction 2.2 Design of Observational Studies 2.2.1 Cross-Sectional Study 2.2.2 Case-Control Study 2.2.3 Cohort Study 2.3 Design of Experimental Studies 2.3.1 Statistical Principles of Experimental Study Design 2.3.1.1 Randomization 2.3.1.2 Control 2.3.1.3 Replication 2.3.2 Basic Elements of Experimental Study Design 2.3.2.1 Treatment 2.3.2.2 Subject 2.3.2.3 Effect 2.3.3 Common Experimental Designs 2.3.3.1 Completely Randomized Design 2.3.3.2 Randomized Paired Design 2.3.3.3 Randomized Block Design 2.3.4 Clinical Trials 2.3.5 Quasi-Experiments 2.4 Sample Size 2.4.1 Experimental Sample Size: Proportion 2.4.1.1 Sample Size for Studies with One Proportion 2.4.1.2 Sample Size for Studies with Two Proportions 2.4.2 Experimental Sample Size: Mean 2.4.2.1 Sample Size for Studies with One Mean 2.4.2.2 Sample Size for Studies with Two Means 2.4.3 Estimation of Sample Size for a Case-Control Study 2.5 Selection of Statistical Methods 2.5.1 The Basic Rules of Selecting Statistical Methods 2.5.1.1 If There Is a Clear Research Purpose, There Would Be a Clear Analysis Goal 2.5.1.2 Select a Statistical Method According to the Type of the Study Design 2.5.1.3 Select a Statistical Method According to the Type of Data 2.5.2 Case Analysis Chapter 3: Statistical Tables and Graphs 3.1 Introduction 3.2 Structures and Types of Tables 3.3 Basic Rules and Demands for Tables 3.4 Making Tables Using SPSS 3.5 Basic Rules and Demands for Graphs 3.6 Types of Common Charts 3.6.1 Bar Chart 3.6.1.1 A Simple Bar Chart 3.6.1.2 Clustered Bar Chart 3.6.1.3 Stacked Bar Chart 3.6.1.4 Percentage Bar Chart 3.6.2 Histograms 3.6.3 Stem-and-Leaf Plot 3.6.4 Pie Chart 3.6.5 Line Chart 3.6.6 Scatter Plot 3.6.7 Box Plot 3.6.8 Mean and Standard Error Chart Chapter 4: Descriptive Statistics of Continuous Variables 4.1 Introduction 4.2 Distribution 4.2.1 Frequency Table 4.2.2 Characteristics of Distribution 4.2.3 Types of Distribution 4.3 Measures of Location 4.3.1 Arithmetic Mean 4.3.2 Geometric Mean 4.3.3 Median 4.4 Measures of Variation 4.4.1 Range 4.4.2 Interquartile Range 4.4.3 Variance and Standard Deviation 4.4.4 Coefficient of Variation 4.5 Normal Distribution 4.5.1 Characteristics of the Normal Distribution 4.5.2 The Standard Normal Distribution 4.5.3 Application of Normal Distribution 4.6 Application 4.6.1 Opening a SPSS Data File 4.6.2 Conducting a Normality Test Using SPSS 4.6.3 Descriptive Statistics Chapter 5: Description of Categorical Variables 5.1 Introduction 5.2 Ratio, Frequency, and Intensity 5.2.1 Ratio 5.2.2 Relative Frequency 5.2.3 Intensity 5.3 Crude Death Rate and Standardization 5.3.1 Direct Method of Standardization 5.3.2 Indirect Method of Standardization 5.3.3 The Use of Standardized Rates Chapter 6: Inferential Statistics: Confidence Interval 6.1 Introduction 6.2 t-Distribution and Binomial Distribution 6.2.1 Sampling Distribution and Standard Error 6.2.2 t-Distribution 6.2.3 Binomial Distribution 6.3 Central Limit Theorem 6.4 Confidence Interval 6.4.1 Confidence Interval for a Mean 6.4.2 Confidence Interval for a Proportion Chapter 7: Inferential Statistics: t-Tests 7.1 Introduction 7.2 Hypothesis Testing 7.2.1 Null Hypothesis and Alternative Hypothesis 7.2.2 Test Statistic 7.2.3 P-Values 7.2.4 One-Sided Test and Two-Sided Test 7.3 One-Sample t-Test 7.3.1 Assumptions of a One-Sample t-Test 7.3.2 Procedure for a One-Sample t-Test 7.4 Paired-Sample t-Test 7.5 Two-Sample t-Test 7.6 The F Test for Equal Variances of Two Groups of Data 7.7 Two Types of Error and Power 7.7.1 Type I Error and Type II Error 7.7.2 Power 7.8 Applications 7.8.1 One-Sample t-Test 7.8.1.1 Selected Output 7.8.1.2 Explanation 7.8.2 Paired-Sample t-Test 7.8.2.1 Selected Output 7.8.2.2 Explanation 7.8.3 Two-Sample T-Test 7.8.3.1 Selected Output 7.8.3.2 Explanation Chapter 8: Analysis of Variance 8.1 Introduction 8.2 The Basic Idea of ANOVA 8.2.1 The Theme of ANOVA 8.2.2 Assumptions of ANOVA 8.2.3 Attentions 8.3 One-Way Analysis of Variance 8.3.1 Completely Randomized Design 8.3.2 Variability Disassembly 8.3.3 Steps of ANOVA Analysis 8.3.4 Example 8.4 Multiple Comparisons 8.4.1 SNK-q Test 8.4.2 LSD-t Test 8.4.3 Dunnett-t Test 8.5 Randomized Block Design ANOVA 8.5.1 Randomized Block Design 8.5.2 Variability Disassembly 8.5.3 Example 8.6 Application 8.6.1 Example of One-way ANOVA 8.6.1.1 Build a SPSS Data File 8.6.1.2 One-Way ANOVA by SPSS 20.0 8.6.1.3 Main Outputs of One-Way ANOVA by SPSS 8.6.1.4 Conclusion 8.6.2 Example of Completely Randomized Block Design ANOVA 8.6.2.1 Build a SPSS Data File 8.6.2.2 Randomized Block ANOVA by SPSS 8.6.2.3 Main Outputs of Randomized Block ANOVA 8.6.2.4 Conclusion 8.7 Chapter Summary Chapter 9: Chi-Square Test 9.1 Introduction 9.1.1 Chi-Square Distribution 9.1.2 Basic Idea of Chi-Square Test 9.2 Two-Independent Samples Chi-Square Test 9.2.1 Data Format 9.2.2 Formulas 9.2.3 Example 9.2.4 Application of Software 9.3 Paired Design Chi-Square Test 9.3.1 Data Format 9.3.2 Formulas 9.3.3 Example 9.3.4 Application of Software 9.4 Chi-Square Test for R × C Table 9.4.1 Data Format 9.4.2 Formulas 9.4.3 Example 9.4.4 Application of Software Chapter 10: Nonparametric Tests 10.1 Introduction to Nonparametric Statistics 10.2 Wilcoxon’s Matched Pairs Test 10.2.1 Introduction 10.2.2 Method 10.2.3 Application of Software 10.3 Tests of Differences Between Two Groups 10.3.1 Introduction 10.3.2 Method 10.3.3 Application of Software 10.4 Tests of Differences Between K Groups (Independent Samples) 10.4.1 Introduction 10.4.2 Method 10.4.3 Application of Software 10.5 Tests of Differences Between K Groups (Nominal Explanatory and Ordinal Variable) 10.5.1 Introduction 10.5.2 Method 10.5.3 Application of Software Chapter 11: Correlation and Simple Linear Regression 11.1 Introduction 11.2 Correlation Analysis 11.2.1 Scatter Plots 11.2.2 Pearson’s Correlation Coefficient 11.2.3 Spearman’s Rank Correlation Coefficient 11.3 Application of Correlation Analysis 11.3.1 Build a SPSS Data File 11.3.2 Pearson’s Correlation by SPSS 11.3.3 Main output results 11.4 Simple Linear Regression 11.4.1 Introduction to Simple Linear Regression 11.4.2 Estimating the Regression Coefficient and Hypothesis Testing 11.4.3 Hypothesis Testing of a Regression Equation 11.5 Application 11.5.1 Build a SPSS Data File 11.5.2 Simple Linear Regression by SPSS 11.5.3 Main Output Results 11.5.4 Conclusion Chapter 12: Multiple Linear Regression Analysis 12.1 Introduction 12.2 Introduction to Multiple Linear Regression 12.2.1 Data Structure 12.2.2 Dummy Variable 12.2.3 Prerequisite and Residual Analysis 12.3 Multiple Linear Regression 12.3.1 Multiple Linear Regression Equation 12.3.2 Hypothesis Testing of Regression Equation 12.3.3 Estimate of Regression Coefficient and Hypothesis Testing 12.3.4 Variable Selection 12.3.5 Collinearity Diagnostics 12.3.6 Interaction 12.4 Application 12.4.1 Build a SPSS Data File 12.4.2 Multiple Linear Regression by SPSS 12.4.3 Main Output Results 12.4.4 Conclusion Chapter 13: Logistic Regression 13.1 Introduction 13.2 Logistic Regression 13.2.1 From Linear Regression to Logistic Regression 13.2.2 Logit Transformation 13.2.3 Odds and Logit Transformation 13.3 Logistic Regression Model 13.3.1 Estimation and Interpretation of Regression Coefficients 13.3.2 Hypothesis Testing of Equations 13.3.3 Hypothesis Testing of Coefficients 13.3.4 Confidence Interval Estimation of Coefficient 13.3.5 Model Selection 13.4 Applications 13.4.1 Build a SPSS Data File 13.4.2 Logistic Regression Using SPSS 13.4.3 Main Output Results 13.4.4 Conclusion Chapter 14: Survival Analysis 14.1 Basic Concepts 14.1.1 Survival Time 14.1.2 Probability of Death and Survival 14.1.3 Survival Function and Hazard Function 14.1.4 Survival Curve, Hazard Curve, and Median Survival Time 14.2 Estimation of Survival Function 14.2.1 Kaplan–Meier Estimates 14.2.2 Life Table Estimation 14.2.3 Interval Estimation of Survival Rate 14.3 Comparison of Survival Curves 14.3.1 Log-Rank Test 14.3.2 Practical Notes 14.4 Application 14.4.1 Kaplan–Meier Procedure 14.4.2 Life Tables Procedure Chapter 15: Cox Regression 15.1 Introduction 15.2 Introduction to Cox Regression 15.2.1 Data Structure 15.2.2 The General Form of Cox Regression 15.2.3 Why Cox Model is Popular 15.3 Principles of Cox Regression 15.3.1 The Hazard Ratio (HR) 15.3.2 Maximum Likelihood (ML) Estimates 15.3.3 Hypothesis Testing and Confidence Interval Estimation 15.3.4 The Meaning of the Proportional Hazard Assumption 15.4 Application 15.4.1 Building a SPSS Data File 15.4.2 Cox Regression Model by SPSS 15.4.3 Main Output Results 15.4.4 Conclusion