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2010030988 contributor B11773761.
2010030988 created "c2011.".
2010030988 date "2011".
2010030988 date "c2011.".
2010030988 dateCopyrighted "c2011.".
2010030988 description "3.2.4. Adjusting for Covariates -- 3.2.5. Pre-Post Comparisons -- 3.2.6. Choosing a Statistic: Time-Course Microarrays -- 3.3. Recommended Approaches -- 3.4. To Learn More -- 4. Biological Background -- 4.1. Medical Imaging -- 4.1.1. Ultrasound -- 4.1.2. EEG/MEG -- 4.1.3. Magnetic Resonance Imaging -- 4.1.3.1. MRI -- 4.1.3.2. fMRI -- 4.1.4. Positron Emission Tomography -- 4.2. Microarrays -- 4.3. To Learn More -- 5. Multiple Tests -- 5.1. Reducing the Number of Hypotheses to Be Tested -- 5.1.1. Normalization -- 5.1.2. Selection Methods -- 5.1.2.1. Univariate Statistics -- 5.1.2.2. Which Statistic? -- 5.1.2.3. Heuristic Methods -- 5.1.2.4. Which Method? -- 5.2. Controlling the Over All Error Rate -- 5.2.1. An Example: Analyzing Data from Microarrays -- 5.3. Controlling the False Discovery Rate -- 5.3.1. An Example: Analyzing Time-Course Data from Microarrays -- 5.4. Gene Set Enrichment Analysis".
2010030988 description "5.5. Software for Performing Multiple Simultaneous Tests -- 5.5.1. AFNI -- 5.5.2. Cyber-T -- 5.5.3. dChip -- 5.5.4. ExactFDR -- 5.5.5. GESS -- 5.5.6. HaploView -- 5.5.7. MatLab -- 5.5.8. R -- 5.5.9. SAM -- 5.5.10. ParaSam -- 5.6. Summary -- 5.7. To Learn More -- 6. The Bootstrap -- 6.1. Samples and Populations -- 6.2. Precision of an Estimate -- 6.2.1. R Code -- 6.2.2. Applying the Bootstrap -- 6.2.3. Bootstrap Reproducibility Index -- 6.2.4. Estimation in Regression Models -- 6.3. Confidence Intervals -- 6.3.1. Testing for Equivalence -- 6.3.2. Parametric Bootstrap -- 6.3.3. Blocked Bootstrap -- 6.3.4. Balanced Bootstrap -- 6.3.5. Adjusted Bootstrap -- 6.3.6. Which Test? -- 6.4. Determining Sample Size -- 6.4.1. Establish a Threshold -- 6.5. Validation -- 6.5.1. Cluster Analysis -- 6.5.2. Correspondence Analysis -- 6.6. Building a Model -- 6.7. How Large Should The Samples Be?".
2010030988 description "6.8. Summary -- 6.9. To Learn More -- 7. Classification Methods -- 7.1. Nearest Neighbor Methods -- 7.2. Discriminant Analysis -- 7.3. Logistic Regression -- 7.4. Principal Components -- 7.5. Naive Bayes Classifier -- 7.6. Heuristic Methods -- 7.7. Decision Trees -- 7.7.1. A Worked-Through Example -- 7.8. Which Algorithm Is Best for Your Application? -- 7.8.1. Some Further Comparisons -- 7.8.2. Validation Versus Cross-validation -- 7.9. Improving Diagnostic Effectiveness -- 7.9.1. Boosting -- 7.9.2. Ensemble Methods -- 7.9.3. Random Forests -- 7.10. Software for Decision Trees -- 7.11. Summary -- 8. Applying Decision Trees -- 8.1. Photographs -- 8.2. Ultrasound -- 8.3. MRI Images -- 8.4. EEGs and EMGs -- 8.5. Misclassification Costs -- 8.6. Receiver Operating Characteristic -- 8.7. When the Categories Are As Yet Undefined -- 8.7.1. Unsupervised Principal Components Applied to fMRI".
2010030988 description "8.7.2. Supervised Principal Components Applied to Microarrays -- 8.8. Ensemble Methods -- 8.9. Maximally Diversified Multiple Trees -- 8.10. Putting It All Together -- 8.11. Summary -- 8.12. To Learn More -- Glossary of Biomedical Terminology -- Glossary of Statistical Terminology -- Appendix: An R Primer -- R1. Getting Started -- R1.1. R Functions -- R1.2. Vector Arithmetic -- R2. Store and Retrieve Data -- R2.1. Storing and Retrieving Files from Within R -- R2.2. The Tabular Format -- R2.3. Comma Separated Format -- R3. Resampling -- R3.1. The While Command -- R4. Expanding R's Capabilities -- R4.1. Downloading Libraries of R Functions -- R4.2. Programming Your Own Functions.".
2010030988 description "Includes bibliographical references and indexes.".
2010030988 description "Machine generated contents note: 1. Very Large Arrays -- 1.1. Applications -- 1.2. Problems -- 1.3. Solutions -- 2. Permutation Tests -- 2.1. Two-Sample Comparison -- 2.1.1. Blocks -- 2.2. k-Sample Comparison -- 2.3. Computing The p-Value -- 2.3.1. Monte Carlo Method -- 2.3.2. An R Program -- 2.4. Multiple-Variable Comparisons -- 2.4.1. Euclidean Distance Matrix Analysis -- 2.4.2. Hotelling's T2 -- 2.4.3. Mantel's U -- 2.4.4. Combining Univariate Tests -- 2.4.5. Gene Set Enrichment Analysis -- 2.5. Categorical Data -- 2.6. Software -- 2.7. Summary -- 3. Applying the Permutation Test -- 3.1. Which Variables Should Be Included? -- 3.2. Single-Value Test Statistics -- 3.2.1. Categorical Data -- 3.2.2. A Multivariate Comparison Based on a Summary Statistic -- 3.2.3. A Multivariate Comparison Based on Variants of Hotelling's T2".
2010030988 extent "xii, 185 p. :".
2010030988 identifier "0470927143 (pbk.)".
2010030988 identifier "9780470927144 (pbk.)".
2010030988 issued "2011".
2010030988 issued "c2011.".
2010030988 language "eng".
2010030988 publisher "Hoboken, N.J. : Wiley,".
2010030988 subject "006.3/12 22".
2010030988 subject "2011 F-685".
2010030988 subject "Biomedical engineering Data processing.".
2010030988 subject "Data Mining.".
2010030988 subject "Data mining.".
2010030988 subject "Diagnostic Imaging.".
2010030988 subject "Functions of several complex variables.".
2010030988 subject "Mathematical statistics.".
2010030988 subject "Models, Statistical.".
2010030988 subject "Oligonucleotide Array Sequence Analysis.".
2010030988 subject "QA76.9.D343 G753 2011".
2010030988 subject "Remote sensing Data processing.".
2010030988 subject "WN 26.5".
2010030988 tableOfContents "3.2.4. Adjusting for Covariates -- 3.2.5. Pre-Post Comparisons -- 3.2.6. Choosing a Statistic: Time-Course Microarrays -- 3.3. Recommended Approaches -- 3.4. To Learn More -- 4. Biological Background -- 4.1. Medical Imaging -- 4.1.1. Ultrasound -- 4.1.2. EEG/MEG -- 4.1.3. Magnetic Resonance Imaging -- 4.1.3.1. MRI -- 4.1.3.2. fMRI -- 4.1.4. Positron Emission Tomography -- 4.2. Microarrays -- 4.3. To Learn More -- 5. Multiple Tests -- 5.1. Reducing the Number of Hypotheses to Be Tested -- 5.1.1. Normalization -- 5.1.2. Selection Methods -- 5.1.2.1. Univariate Statistics -- 5.1.2.2. Which Statistic? -- 5.1.2.3. Heuristic Methods -- 5.1.2.4. Which Method? -- 5.2. Controlling the Over All Error Rate -- 5.2.1. An Example: Analyzing Data from Microarrays -- 5.3. Controlling the False Discovery Rate -- 5.3.1. An Example: Analyzing Time-Course Data from Microarrays -- 5.4. Gene Set Enrichment Analysis".
2010030988 tableOfContents "5.5. Software for Performing Multiple Simultaneous Tests -- 5.5.1. AFNI -- 5.5.2. Cyber-T -- 5.5.3. dChip -- 5.5.4. ExactFDR -- 5.5.5. GESS -- 5.5.6. HaploView -- 5.5.7. MatLab -- 5.5.8. R -- 5.5.9. SAM -- 5.5.10. ParaSam -- 5.6. Summary -- 5.7. To Learn More -- 6. The Bootstrap -- 6.1. Samples and Populations -- 6.2. Precision of an Estimate -- 6.2.1. R Code -- 6.2.2. Applying the Bootstrap -- 6.2.3. Bootstrap Reproducibility Index -- 6.2.4. Estimation in Regression Models -- 6.3. Confidence Intervals -- 6.3.1. Testing for Equivalence -- 6.3.2. Parametric Bootstrap -- 6.3.3. Blocked Bootstrap -- 6.3.4. Balanced Bootstrap -- 6.3.5. Adjusted Bootstrap -- 6.3.6. Which Test? -- 6.4. Determining Sample Size -- 6.4.1. Establish a Threshold -- 6.5. Validation -- 6.5.1. Cluster Analysis -- 6.5.2. Correspondence Analysis -- 6.6. Building a Model -- 6.7. How Large Should The Samples Be?".
2010030988 tableOfContents "6.8. Summary -- 6.9. To Learn More -- 7. Classification Methods -- 7.1. Nearest Neighbor Methods -- 7.2. Discriminant Analysis -- 7.3. Logistic Regression -- 7.4. Principal Components -- 7.5. Naive Bayes Classifier -- 7.6. Heuristic Methods -- 7.7. Decision Trees -- 7.7.1. A Worked-Through Example -- 7.8. Which Algorithm Is Best for Your Application? -- 7.8.1. Some Further Comparisons -- 7.8.2. Validation Versus Cross-validation -- 7.9. Improving Diagnostic Effectiveness -- 7.9.1. Boosting -- 7.9.2. Ensemble Methods -- 7.9.3. Random Forests -- 7.10. Software for Decision Trees -- 7.11. Summary -- 8. Applying Decision Trees -- 8.1. Photographs -- 8.2. Ultrasound -- 8.3. MRI Images -- 8.4. EEGs and EMGs -- 8.5. Misclassification Costs -- 8.6. Receiver Operating Characteristic -- 8.7. When the Categories Are As Yet Undefined -- 8.7.1. Unsupervised Principal Components Applied to fMRI".
2010030988 tableOfContents "8.7.2. Supervised Principal Components Applied to Microarrays -- 8.8. Ensemble Methods -- 8.9. Maximally Diversified Multiple Trees -- 8.10. Putting It All Together -- 8.11. Summary -- 8.12. To Learn More -- Glossary of Biomedical Terminology -- Glossary of Statistical Terminology -- Appendix: An R Primer -- R1. Getting Started -- R1.1. R Functions -- R1.2. Vector Arithmetic -- R2. Store and Retrieve Data -- R2.1. Storing and Retrieving Files from Within R -- R2.2. The Tabular Format -- R2.3. Comma Separated Format -- R3. Resampling -- R3.1. The While Command -- R4. Expanding R's Capabilities -- R4.1. Downloading Libraries of R Functions -- R4.2. Programming Your Own Functions.".
2010030988 tableOfContents "Machine generated contents note: 1. Very Large Arrays -- 1.1. Applications -- 1.2. Problems -- 1.3. Solutions -- 2. Permutation Tests -- 2.1. Two-Sample Comparison -- 2.1.1. Blocks -- 2.2. k-Sample Comparison -- 2.3. Computing The p-Value -- 2.3.1. Monte Carlo Method -- 2.3.2. An R Program -- 2.4. Multiple-Variable Comparisons -- 2.4.1. Euclidean Distance Matrix Analysis -- 2.4.2. Hotelling's T2 -- 2.4.3. Mantel's U -- 2.4.4. Combining Univariate Tests -- 2.4.5. Gene Set Enrichment Analysis -- 2.5. Categorical Data -- 2.6. Software -- 2.7. Summary -- 3. Applying the Permutation Test -- 3.1. Which Variables Should Be Included? -- 3.2. Single-Value Test Statistics -- 3.2.1. Categorical Data -- 3.2.2. A Multivariate Comparison Based on a Summary Statistic -- 3.2.3. A Multivariate Comparison Based on Variants of Hotelling's T2".
2010030988 title "Analyzing the large numbers of variables in biomedical and satellite imagery / Phillip I. Good.".
2010030988 type "text".