Introduction to biostatistical applications in health research with Microsoft Office Excel and R. (2020)

• Record Type: Book
• Further Information: Note: Robert P. Hirsch.
• Authors: Hirsch, Robert P
• Contents: Preface PART ONE: Basic Concepts 1.Thinking About Chance 1.1.Properties of Chance 1.2.Combinations of events 1.2.1 Intersections 1.2.2 Unions 1.3.Bayes’ theorem 2.Describing Populations 2.1.Types of data 2.2.Describing distributions graphically 2.2.1. Graphing discrete data 2.2.2. Graphing continuous data 2.2.3. Frequency polygon 2.3.Describing distributions mathematically 2.3.1. Parameter of location 2.3.2. Parameter of dispersion 2.4 Taking chance into account 2.4.1 Standard normal distribution 3.Examining Samples 3.1.Nature of samples 3.2.Estimation 3.2.1 Point estimates 3.2.2 The sampling distribution 3.2.3 Interval estimates 3.3.Hypothesis testing PART TWO: Univariable Analysis 4.Univariable Analysis of a Continuous Dependent Variable 4.1.Student’s t distribution 4.2.Interval estimation 4.3.Hypothesis testing 5.Univariable Analysis of an Ordinal Dependent Variable 5.1 Nonparametric methods 5.2 Estimation 5.3 Wilcoxon signed-rank test 5.4 Statistical power of nonparametric tests 6.Univariable Analysis of a Nominal Dependent Variable 6.1.Distributions of nominal data 6.2.Point estimates 6.2.1 Proportions 6.2.2 Rates 6.3.Sampling distributions 6.3.1 Binomial distribution 6.3.2 Poisson distribution 6.4.Interval estimation 6.5.Hypothesis testing PART THREE: Bivariable Analysis 7.Bivariable Analysis of a Continuous Dependent Variable 7.1.Continuous independent variable 7.1.1 Regression analysis 7.1.2 Correlation analysis 7.2.Ordinal independent variable 7.3.Nominal independent variable 7.3.1 Estimating the difference between groups 7.3.2 Taking chance into account 8.Bivariable Analysis of an Ordinal Dependent Variable 8.1.Ordinal independent variable 8.2.Nominal independent variable 9.Bivariable Analysis of a Nominal Dependent Variable 9.1.Continuous independent variable 9.1.1 Estimation 9.1.2 Hypothesis testing 9.2.Nominal independent variable 9.2.1 Dependent variable not affected by time: Unpaired design 9.2.2 Dependent variable not affected by time: Paired design 9.2.3 Dependent variable affected by time PART FOUR: Multivariable Analysis 10.Multivariable Analysis of a Continuous Dependent Variable 10.1.Continuous independent variables 10.1.1 Multiple regression analysis 10.1.2 Multiple correlation analysis 10.2.Nominal independent variables 10.2.1 Analysis of variance 10.2.2 Posterior tests 10.3.Continuous and nominal independent variables 10.3.1 Indicator (“dummy”) variables 10.3.2 Interaction variables 10.3.3 General linear model 11.Multivariable Analysis of an Ordinal Dependent Variable 11.1.Nonparametric ANOVA 11.2.Posterior testing 12.Multivariable Analysis of a Nominal Dependent Variable 12.1.Continuous and/or nominal independent variables 12.1.1 Maximum likelihood estimation 12.1.2 Logistic regression analysis 12.1.3 Cox regression analysis 12.2.Nominal independent variables 12.2.1 Stratified analysis 12.2.2 Life table analysis 13. Testing Assumptions 13.1Continuous dependent variables 13.1.1 Assuming a Gaussian distribution 13.1.2 Transforming dependent variables 13.1.3 Assuming equal variances 13.1.4 Assuming additive relationships 13.2Nominal dependent variables 13.2.1 Assuming a Gaussian distribution 13.2.2 Assuming equal variances 13.2.3 Assuming additive relationships 13.3Independent variables
• Edition: Second edition
• Publisher Details: Hoboken : John Wiley & Sons, Inc
• Publication Date: 2020
• Extent: 1 online resource
• Subjects: 610.285; Medical statistics; Biometry; Electronic spreadsheets -- Computer programs; Biometry -- Problems, exercises, etc; Medical statistics -- Problems, exercises, etc
• Languages: English
• ISBNs: 9781119722649; 9781119722625
• Related ISBNs: 9781119722595
• Notes: Note: Description based on CIP data; resource not viewed.
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