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Introduction to Biostatistical Applications in Health Research with Microsoft Office Excel [Kõva köide]

  • Formaat: Hardback, 416 pages, kõrgus x laius x paksus: 239x158x28 mm, kaal: 748 g
  • Ilmumisaeg: 15-Apr-2016
  • Kirjastus: John Wiley & Sons Inc
  • ISBN-10: 1119089654
  • ISBN-13: 9781119089650
Teised raamatud teemal:
  • Formaat: Hardback, 416 pages, kõrgus x laius x paksus: 239x158x28 mm, kaal: 748 g
  • Ilmumisaeg: 15-Apr-2016
  • Kirjastus: John Wiley & Sons Inc
  • ISBN-10: 1119089654
  • ISBN-13: 9781119089650
Teised raamatud teemal:
A practical and methodological approach to the statistical logic of biostatistics in the field of health research

Focusing on a basic understanding of the methods and analyses in health research, Introduction to Biostatistical Applications in Health Research with Microsoft® Office Excel® 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.

The book is constructed around a flowchart that outlines the appropriate circumstances for selecting a method to analyze a specific set of data. Beginning with an introduction to the foundational methods of statistical logic before moving on to more complex methods, Introduction to Biostatistical Applications in Health Research with Microsoft® Office Excel® also includes:





Detailed discussions of how knowledge and skills in health research have been integrated with biostatistical methods Numerous examples with clear explanations that use mostly real-world health research data in order to provide a better understanding of the practical applications Implements Excel graphic representations throughout to help readers evaluate and analyze individual results An appendix with basic information on how to use Excel A companion website with additional Excel files, data sets, and homework problems as well as an Instructors Solutions Manual

Introduction to Biostatistical Applications in Health Research with Microsoft® Office Excel® is an excellent textbook for upper-undergraduate and graduate-level courses in biostatistics and public health. In addition, the book is an appropriate reference for both health researchers and professionals.
Preface ix
Acknowledgements xi
Notices xiii
About The Companion Website xv
PART ONE BASIC CONCEPTS
1(74)
1 Thinking About Chance
3(15)
1.1 Properties of Probability
3(4)
1.2 Combinations of Events
7(8)
1.2.1 Intersections
8(5)
1.2.2 Unions
13(2)
1.3 Bayes' Theorem
15(3)
2 Describing Distributions
18(31)
2.1 Types of Data
19(1)
2.2 Describing Distributions Graphically
19(7)
2.2.1 Graphing Discrete Data
20(2)
2.2.2 Graphing Continuous Data
22(4)
2.3 Describing Distributions Mathematically
26(12)
2.3.1 Parameter of Location
27(4)
2.3.2 Parameter of Dispersion
31(7)
2.4 Taking Chance into Account
38(11)
2.4.1 Standard Normal Distribution
39(10)
3 Examining Samples
49(26)
3.1 Nature of Samples
50(1)
3.2 Estimation
51(13)
3.2.1 Point Estimates
51(5)
3.2.2 The Sampling Distribution
56(4)
3.2.3 Interval Estimates
60(4)
3.3 Hypothesis Testing
64(11)
3.3.1 Relationship between Interval Estimation and Hypothesis Testing
72(3)
PART TWO UNIVARIABLE ANALYSES
75(46)
4 Univariable Analysis Of A Continuous Dependent Variable
79(11)
4.1 Student's t-Distribution
81(3)
4.2 Interval Estimation
84(2)
4.3 Hypothesis Testing
86(4)
5 Univariable Analysis Of An Ordinal Dependent Variable
90(9)
5.1 Nonparametric Methods
90(4)
5.2 Estimation
94(1)
5.3 Wilcoxon Signed-Rank Test
95(2)
5.4 Statistical Power of Nonparametric Tests
97(2)
6 Univariable Analysis Of A Nominal Dependent Variable
99(22)
6.1 Distribution of Nominal Data
100(1)
6.2 Point Estimates
101(7)
6.2.1 Proportions
101(3)
6.2.2 Rates
104(4)
6.3 Sampling Distributions
108(6)
6.3.1 Binomial Distribution
108(4)
6.3.2 Poisson Distribution
112(2)
6.4 Interval Estimation
114(3)
6.5 Hypothesis Testing
117(4)
PART THREE BIVARIABLE ANALYSES
121(106)
7 Bivariable Analysis of a Continuous Dependent Variable
123(52)
7.1 Continuous Independent Variable
123(42)
7.1.1 Regression Analysis
125(24)
7.1.2 Correlation Analysis
149(16)
7.2 Ordinal Independent Variable
165(1)
7.3 Nominal Independent Variable
166(9)
7.3.1 Estimating the Difference between the Groups
166(1)
7.3.2 Taking Chance into Account
167(8)
8 Bivariable Analysis of an Ordinal Dependent Variable
175(14)
8.1 Ordinal Independent Variable
176(8)
8.2 Nominal Independent Variable
184(5)
9 Bivariable Analysis of a Nominal Dependent Variable
189(38)
9.1 Continuous Independent Variable
190(10)
9.1.1 Estimation
191(7)
9.1.2 Hypothesis Testing
198(2)
9.2 Nominal Independent Variable
200(27)
9.2.1 Dependent Variable Not Affected by Time: Unpaired Design
201(7)
9.2.2 Hypothesis Testing
208(10)
9.2.3 Dependent Variable Not Affected by Time: Paired Design
218(5)
9.2.4 Dependent Variable Affected by Time
223(4)
PART FOUR MULTIVARIABLE ANALYSES
227(108)
10 Multivariable Analysis of a Continuous Dependent Variable
229(52)
10.1 Continuous Independent Variables
230(18)
10.1.1 Multiple Regression Analysis
231(16)
10.1.2 Multiple Correlation Analysis
247(1)
10.2 Nominal Independent Variables
248(17)
10.2.1 Analysis of Variance
249(9)
10.2.2 Posterior Testing
258(7)
10.3 Both Continuous and Nominal Independent Variables
265(16)
10.3.1 Indicator (Dummy) Variables
266(1)
10.3.2 Interaction Variables
267(6)
10.3.3 General Linear Model
273(8)
11 Multivariable Analysis of an Ordinal Dependent Variable
281(12)
11.1 Nonparametric Analysis of Variance
282(6)
11.2 Posterior Testing
288(5)
12 Multivariable Analysis of a Nominal Dependent Variable
293(42)
12.1 Continuous And/or Nominal Independent Variables
294(13)
12.1.1 Maximum Likelihood Estimation
294(3)
12.1.2 Logistic Regression Analysis
297(9)
12.1.3 Cox Regression Analysis
306(1)
12.2 Nominal Independent Variables
307(28)
12.2.1 Stratified Analysis
308(10)
12.2.2 Relationship between Stratified Analysis and Logistic Regression
318(4)
12.2.3 Life Table Analysis
322(13)
Appendix A Flowcharts 335(6)
Appendix B Statistical Tables 341(36)
Appendix C Standard Distributions 377(3)
Appendix D Excel Primer 380(5)
Index 385
Robert P. Hirsch, PhD, 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.