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Introduction to Biostatistical Applications in Health Research with Microsoft Office Excel Set [Kietas viršelis]

  • Formatas: Hardback, 648 pages, aukštis x plotis x storis: 229x150x15 mm, weight: 352 g
  • Išleidimo metai: 19-Jan-2018
  • Leidėjas: John Wiley & Sons Inc
  • ISBN-10: 1119090040
  • ISBN-13: 9781119090045
Kitos knygos pagal šią temą:
Introduction to Biostatistical Applications in Health Research with Microsoft Office Excel SetDidesnis paveikslėlis
  • Formatas: Hardback, 648 pages, aukštis x plotis x storis: 229x150x15 mm, weight: 352 g
  • Išleidimo metai: 19-Jan-2018
  • Leidėjas: John Wiley & Sons Inc
  • ISBN-10: 1119090040
  • ISBN-13: 9781119090045
Kitos knygos pagal šią temą:
Pastovi nuoroda: https://www.kriso.lt/db/9781119090045.html
Raktažodžiai:
This set includes Introduction to Biostatistical Applications in Health Research with Microsoft Office Excel and Workbook to accompany Introduction to Biostatistical Applications in Health Research with Microsoft Office Excel.

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 Microsoft Office 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 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 Instructor’s Solutions Manual
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
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
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
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
Preface ix
Acknowledgements xi
Notices xiii
1 Thinking about Chance
1(12)
1.1
Chapter Summary
1(2)
1.2 Glossary
3(2)
1.3 Equations
5(1)
1.4 Examples
6(4)
1.5 Exercises
10(3)
2 Describing Populations
13(11)
2.1
Chapter Summary
13(3)
2.2 Glossary
16(2)
2.3 Equations
18(1)
2.4 Examples
18(4)
2.5 Exercises
22(2)
3 Examining Samples
24(12)
3.1
Chapter Summary
24(3)
3.2 Glossary
27(1)
3.3 Equations
28(1)
3.4 Examples
29(3)
3.5 Exercises
32(4)
4 Univariable Analysis of a Continuous Dependent Variable
36(9)
4.1
Chapter Summary
36(1)
4.2 Glossary
37(1)
4.3 Equations
38(1)
4.4 Examples
38(3)
4.5 Exercises
41(4)
5 Univariable Analysis of an Ordinal Dependent Variable
45(7)
5.1
Chapter Summary
45(1)
5.2 Glossary
46(1)
5.3 Equations
47(1)
5.4 Examples
47(3)
5.5 Exercises
50(2)
6 Univariable Analysis of a Nominal Dependent Variable
52(10)
6.1
Chapter Summary
52(1)
6.2 Glossary
53(1)
6.3 Equations
54(1)
6.4 Examples
55(3)
6.5 Exercises
58(4)
7 Blvarlable Analysis of a Continuous Dependent Variable
62(20)
7.1
Chapter Summary
62(4)
7.2 Glossary
66(2)
7.3 Equations
68(1)
7.4 Examples
69(8)
7.5 Exercises
77(5)
8 Bivariable Analysis of an Ordinal Dependent Variable
82(8)
8.1
Chapter Summary
82(1)
8.2 Glossary
83(1)
8.3 Equations
84(1)
8.4 Examples
84(3)
8.5 Exercises
87(3)
9 Blvarlable Analysis of a Nominal Dependent Variable
90(15)
9.1
Chapter Summary
90(2)
9.2 Glossary
92(1)
9.3 Equations
93(1)
9.4 Examples
94(6)
9.5 Exercises
100(5)
10 Multlvariable Analysis of a Continuous Dependent Variable
105(27)
10.1
Chapter Summary
105(3)
10.2 Glossary
108(1)
10.3 Equations
109(1)
10.4 Examples
110(14)
10.5 Exercises
124(8)
11 Multlvariable Analysis of an Ordinal Dependent Variable
132(9)
11.1
Chapter Summary
132(1)
11.2 Glossary
133(1)
11.3 Equations
133(1)
11.4 Examples
134(3)
11.5 Exercises
137(4)
12 Multlvariable Analysis of a Nominal Dependent Variable
141(22)
12.1
Chapter Summary
141(3)
12.2 Glossary
144(2)
12.3 Equations
146(1)
12.4 Examples
147(10)
12.5 Exercises
157(6)
13 Selecting Statistical Tests
163(14)
13.1 Overview
163(1)
13.2 Glossary
164(1)
13.3 Examples
165(6)
13.4 Exercises
171(6)
Appendix A Flowcharts 177(6)
Appendix B Statistical Tables 183(36)
Appendix C Answers to Odd Exercises 219(2)
Index 221
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.