Resampling methods: a practical guide to data analysis
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| Main Author: | |
|---|---|
| Format: | Book |
| Language: | English |
| Published: |
Boston ; Basel ; Berlin
Birkhäuser
2006
|
| Edition: | 3. ed. |
| Subjects: | |
| Links: | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=022106774&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
| Item Description: | Literaturverz. S. 195 - 207 |
| Physical Description: | XVI, 218 S. Ill., graph. Darst. |
| ISBN: | 0817643869 9780817643867 |
Staff View
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Record in the Search Index
| _version_ | 1819271250318458880 |
|---|---|
| adam_text | Titel: Resampling methods
Autor: Good, Phillip I
Jahr: 2006
Contents
Preface to the Third Edition........................................ xi
Preface to the Second Edition....................................... xiii
Preface to the First Edition......................................... xv
Which Chapter Should I Read?..................................... xvii
1 Software for Resampling....................................... 1
1.1 Box Sampler®: An Excel Add-In............................... 1
1.2 C++........................................................ 2
1.3 CART®..................................................... 2
1.4 EViews..................................................... 2
1.5 MatLab®.................................................... 2
1.6 R.......................................................... 2
1.7 Resampling Stats®............................................ 2
1.8 SAS®....................................................... 3
1.9 S-PLUS®.................................................... 3
1.10 Stata®....................................................... 3
1.11 Statistical Calculator.......................................... 3
1.12 StatXact®................................................... 4
1.13 Xlminer®.................................................... 4
1.14 Miscellaneous............................................... 4
2 Estimating Population Parameters.............................. 5
2.1 Population Parameters ........................................ 5
2.1.1 Frequency Distribution and Percentiles.................... 5
2.1.2 Central Values......................................... 6
2.1.3 Measures of Dispersion................................. 7
2.2 Samples and Populations...................................... 8
2.2.1 The Bootstrap......................................... 8
2.2.2 Programming the Bootstrap.............................. 10
Contents
2.2.3 Estimating Bias........................................ 16
2.2.4 An Example .......................................... 17
2.3 Confidence Intervals.......................................... 17
2.3.1 Limitations of the Percentile Bootstrap Confidence Interval... 18
2.3.2 The Bias-Corrected Bootstrap Confidence Interval .......... 18
2.3.3 Computer Code: The BCa Bootstrap...................... 19
2.3.4 The Bootstrap-t........................................ 20
2.3.5 Parametric Bootstrap................................... 21
2.3.6 Smoothing the Bootstrap................................ 23
2.3.7 Importance Sampling and the Tilted Bootstrap.............. 25
2.3.8 Iterated Bootstrap...................................... 26
2.4 Summary................................................... 27
2.5 To Learn More............................................... 27
2.6 Exercises ................................................... 28
Comparing Two Populations ................................... 31
3.1 A Laboratory Experiment...................................... 31
3.2 Analyzing the Experiment..................................... 32
3.3 Some Statistical Considerations................................. 34
3.3.1 Framing the Hypothesis................................. 34
3.3.2 Hypothesis Versus Alternative ........................... 34
3.3.3 Unpredictable Variation................................. 34
3.3.4 Some Not-so-Hidden Assumptions ....................... 35
3.3.5 More General Hypotheses............................... 36
3.4 Computing the p-Value........................................ 37
3.4.1 Monte Carlo.......................................... 37
3.4.2 Program Code......................................... 38
3.4.3 One-Sided Versus Two-Sided Test........................ 42
3.5 Matched Pairs ............................................... 43
3.6 Unequal Variances............................................ 46
3.6.1 Underlying Assumptions................................ 51
3.7 Comparing Variances......................................... 51
3.7.1 Unequal Sample Sizes.................................. 55
3.8 To Learn More............................................... 56
3.9 Exercises ................................................... 57
Choosing the Best Procedure................................... 61
4.1 Why You Need to Read This Chapter............................ 61
4.2 Fundamental Concepts........................................ 63
4.2.1 Two Types of Error..................................... 63
4.2.2 Losses............................................... 64
4.2.3 Significance Level and Power............................ 65
4.2.4 What Significance Level Should I Use?.................... 66
4.3 Confidence Intervals.......................................... 67
4.3.1 Interpreting the Confidence Interval....................... 68
4.3.2 Multiple Tests......................................... 68
Contents vii
4.4 Which Test Should Be Used?................................... 69
4.4.1 Types of Data......................................... 69
4.4.2 Assumptions.......................................... 69
4.4.3 Recognizing Common Parametric Distributions............. 70
4.4.4 Transformations....................................... 71
4.4.5 Distribution-Free Tests.................................. 72
4.4.6 Which Test? .......................................... 73
4.5 Summary................................................... 73
4.6 To Learn More............................................... 73
4.7 Exercises ................................................... 74
Experimental Design and Analysis .............................. 77
5.1 Separating Signal from Noise .................................. 77
5.1.1 Blocking............................................. 77
5.1.2 Analyzing a Blocked Experiment......................... 78
5.1.3 Measuring Factors We Can t Control...................... 81
5.1.4 Randomization........................................ 82
5.2 k-Sample Comparison......................................... 82
5.2.1 Testing for Any and All Differences....................... 82
5.2.2 Analyzing a One-Way Table............................. 83
5.2.3 Ordered Alternatives................................... 85
5.2.4 Calculating Pitman Correlation........................... 87
5.2.5 Effect of Ties.......................................... 88
5.3 Balanced Designs ............................................ 89
5.3.1 Main Effects.......................................... 89
5.3.2 Analyzing a Two-Way Table............................. 90
5.3.3 Testing for Interactions ................................. 91
5.3.4 Synchronized Rearrangements........................... 92
5.3.5 A Worked-Through Example............................ 93
5.4 Designing an Experiment...................................... 96
5.4.1 Latin Square.......................................... 97
5.5 Determining Sample Size...................................... 99
5.5.1 Group Sequential Designs............................... 100
5.6 Unbalanced Designs..........................................102
5.6.1 Multidimensional Contingency Tables..................... 103
5.6.2 Missing Combinations..................................104
5.7 Summary...................................................105
5.8 To Learn More...............................................105
5.9 Exercises ...................................................106
Categorical Data ............................................. 109
6.1 Fisher s Exact Test ........................................... 109
6.1.1 Computing Fisher s Exact Test...........................Ill
6.1.2 One-Tailed and Two-Tailed Tests......................... 112
6.1.3 The Two-Tailed Test.................................... 112
6.1.4 When to Accept....................................... 113
Contents
6.1.5 Is the Sample Large Enough?............................114
6.2 Odds Ratio..................................................115
6.2.1 Stratified 2 x 2 s.......................................117
6.3 Exact Significance Levels......................................119
6.4 Unordered r x c Contingency Tables............................119
6.4.1 Test of Association..................................... 121
6.4.2 Causation Versus Association............................ 122
6.5 Ordered Statistical Tables...................................... 123
6.5.1 More Than Two Rows and Two Columns.................. 124
6.6 Summary................................................... 126
6.7 To Learn More............................................... 126
6.8 Exercises ................................................... 127
Multiple Variables and Multiple Hypotheses...................... 129
7.1 Single-Valued Test Statistic....................................129
7.1.1 Applications to Repeated Measures.......................131
7.1.2 An Example ..........................................133
7.2 Combining Univariate Tests....................................133
7.3 The Generalized Quadratic Form ...............................134
7.3.1 Mantel s U............................................ 134
7.3.2 Example in Epidemiology............................... 135
7.3.3 Further Generalization.................................. 135
7.3.4 The MRPP Statistic.................................... 136
7.3.5 An Example: Blue Grouse Migration Data................. 136
7.4 Multiple Hypotheses.......................................... 138
7.4.1 Testing for Trend...................................... 138
7.5 Summary................................................... 140
7.6 To Learn More............................................... 140
7.7 Exercises ................................................... 141
Model Building............................................... 143
8.1 Picturing Relationships........................................143
8.2 Unpredictable Variation.......................................146
8.2.1 Building a Model......................................146
8.2.2 Bivariate Dependence ..................................148
8.2.3 Confidence Interval for the Correlation Coefficient..........149
8.2.4 But Does the Model Make Sense?........................150
8.2.5 Estimating the Parameters...............................151
8.3 Linear Regression............................................151
8.3.1 Other Regression Methods ..............................155
8.4 Improving the Model .........................................156
8.4.1 Testing for Significance in Multipredictor Regression........ 157
8.4.2 Comparing Two Regression Lines........................ 158
8.4.3 Prediction Error....................................... 160
8.4.4 Correcting for Bias..................................... 161
8.5 Validation................................................... 161
Contents ix
8.5.1 Metrics...............................................161
8.5.2 Cross-Validation.......................................164
8.5.3 Using the Bootstrap for Model Validation..................165
8.6 Summary...................................................166
8.7 To Learn More...............................................166
8.8 Exercises ...................................................167
9 Decision Trees................................................ 171
9.1 Classification................................................171
9.2 Consumer Survey ............................................ 176
9.3 Trees Versus Regression.......................................181
9.3.1 Head-to-Head Comparison..............................182
9.3.2 Which Variables?......................................185
9.4 To Learn More...............................................186
9.5 Exercises ...................................................188
Answers to Selected Exercises ...................................... 189
Bibliography..................................................... 195
Glossary ........................................................ 209
Author Index .................................................... 211
Subject Index.................................................... 215
|
| any_adam_object | 1 |
| author | Good, Phillip I. 1937- |
| author_GND | (DE-588)130601152 |
| author_facet | Good, Phillip I. 1937- |
| author_role | aut |
| author_sort | Good, Phillip I. 1937- |
| author_variant | p i g pi pig |
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| dewey-full | 519.54 |
| dewey-hundreds | 500 - Natural sciences and mathematics |
| dewey-ones | 519 - Probabilities and applied mathematics |
| dewey-raw | 519.54 |
| dewey-search | 519.54 |
| dewey-sort | 3519.54 |
| dewey-tens | 510 - Mathematics |
| discipline | Mathematik |
| edition | 3. ed. |
| format | Book |
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| indexdate | 2024-12-20T15:06:50Z |
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| isbn | 0817643869 9780817643867 |
| language | English |
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| physical | XVI, 218 S. Ill., graph. Darst. |
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| spellingShingle | Good, Phillip I. 1937- Resampling methods a practical guide to data analysis Resampling (DE-588)4288033-6 gnd |
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| title | Resampling methods a practical guide to data analysis |
| title_auth | Resampling methods a practical guide to data analysis |
| title_exact_search | Resampling methods a practical guide to data analysis |
| title_full | Resampling methods a practical guide to data analysis Phillip I. Good |
| title_fullStr | Resampling methods a practical guide to data analysis Phillip I. Good |
| title_full_unstemmed | Resampling methods a practical guide to data analysis Phillip I. Good |
| title_short | Resampling methods |
| title_sort | resampling methods a practical guide to data analysis |
| title_sub | a practical guide to data analysis |
| topic | Resampling (DE-588)4288033-6 gnd |
| topic_facet | Resampling Einführung |
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