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1. |
Record Nr. |
UNINA9911020129703321 |
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Autore |
Cochran William G (William Gemmell), <1909-1980.> |
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Titolo |
Planning and analysis of observational studies / / William G. Cochran ; edited by Lincoln E. Moses and Frederick Mosteller |
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Pubbl/distr/stampa |
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ISBN |
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9786612307997 |
9781282307995 |
1282307991 |
9780470316542 |
0470316543 |
9780470317280 |
0470317280 |
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Descrizione fisica |
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1 online resource (166 p.) |
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Collana |
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Wiley series in probability and mathematical statistics, , 0271-6356 |
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Altri autori (Persone) |
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MosesLincoln E |
MostellerFrederick <1916-2006.> |
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Disciplina |
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Soggetti |
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Analysis of variance |
Experimental design |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Note generali |
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Description based upon print version of record. |
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Nota di bibliografia |
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Includes bibliographies and index. |
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Nota di contenuto |
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Planning and Analysis of Observational Studies; Contents; 1. VARIATION, CONTROL, AND BIAS; 1. I. Introduction; 1.2. Strategy in Controlled Experiments- Sampled and Target Populations; 1.3. The Principal Sources of Variation in the Responses; 1.4. Methods of Control; 1.5. Effects of Bias; 1.6. Summary; References; 2. STATISTICAL INTRODUCTION; 2.1. Drawing Conclusions from Data; 2.2. Tests of Significance; 2.3. Confidence Intervals; 2.4. Systematic Differences Between the Populations; 2.5. The Model When Bias is Present; 2.6. Summary; References; 3. PRELIMINARY ASPECTS OF PLANNING |
3.1. Introdudtion3.2. The Statement of Objectives; 3.3. The Treatments; 3.4. Measurements of Treatment Levels for Individual Persons and the Effects of Grouping; 3.5. Other Points Related to Treatments; 3.6. Control Treatments; 3.7. The Responses; 3.8. Timing of Measurements; 3.9. summary; References; 4. FURTHER ASPECTS OF PLANNING; 4.1. Sample Size in Relation to Tests of Significance; 4.2. Sample Size for |
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Estimation; 4.3. The Effect of Bias; 4.4. More Complex Comparisons; 4.5. Samples of Clusters; 4.6. Plans for Reducing Nonresponse; 4.7. Relationship Between Sampled and Target Populations |
4.8. Pilot Studies and Pretests4.9. The Devil's Advocate; 4.10. Summary; References; 5 . MATCHING; 5.1. Confounding Variables; 5.2. Matching; 5.3. The Construction of Matches; 5.4. Effect of Within-Class Matching on x; 5.5. Effect of Caliper Matching on x; 5.6. Effect of "Nearest Available" Matching on x; 5.7. Effect of Mean Matching on x; 5.8. Effects on bias of y1 - y2; 5.9. Effect of Matching on the Variance of y1 - y2; 5.10. Introduction to Statistical Analysis of Pair-Matched Samples; 5.11. Analysis with Mean Matching: y Continuous; 5.12. summary; References; 6. ADJUSTMENTS IN ANALYSIS |
6.1. Introduction6.2. y Continuous: x's Classified; 6.3. y Binomial: x's Classified; 6.4. Treatment Difference Varying From Cell to Cell; 6.5. y and x's Quantitative: Adjustments by Regression (Covariance); 6.6. Regression Adjustments with Some x's Classified; 6.7. Effect of Regression Adjustments on Bias in y1-y2; 6.8. Effect of Curvature on Linear-Regression Adjustments; 6.9. Effectiveness of Regression Adjustments on Precision; 6.10. Effect of Errors in the Measurement of x; 6.11. Matching and Adjustment Compared: In Experiments |
6.12. Matching and Adjustment Compared: In Observational StudiesAppendix to Section 6.12; 6.13. A Preliminary Test of Comparability; 6.14. Summary; References; 7. SIMPLE STUDY STRUCTURES; 7.1. Introduction; 7.2. The Single Group: Measured After Treatment Only; 7.3. The Single Group: Measured Before and After Treatment; 7.4. The Single Group: Series of Measurements Before and After; References; INDEX |
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Sommario/riassunto |
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Treats studies, primarily in human populations, that show casual effects of certain agents, procedures, treatment or programs. Deals with the difficulties that comparative observational studies have because of bias in their design and analysis. Systematically considers the many sources of bias and discusses how care in matching or adjustment of results can reduce the effects of bias in these investigations. |
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2. |
Record Nr. |
UNISA996691679903316 |
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Autore |
Bianculli Domenico |
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Titolo |
Software Engineering and Formal Methods : 23rd International Conference, SEFM 2025, Toledo, Spain, November 10–14, 2025, Proceedings / / edited by Domenico Bianculli, Elena Gómez-Martínez |
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Pubbl/distr/stampa |
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Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2026 |
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ISBN |
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Edizione |
[1st ed. 2026.] |
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Descrizione fisica |
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1 online resource (475 pages) |
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Collana |
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Lecture Notes in Computer Science, , 1611-3349 ; ; 16192 |
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Disciplina |
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Soggetti |
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Software engineering |
Logic programming |
Data structures (Computer science) |
Information theory |
Microprogramming |
Computer systems |
Computer programming |
Software Engineering |
Logic in AI |
Data Structures and Information Theory |
Control Structures and Microprogramming |
Computer System Implementation |
Programming Techniques |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Nota di contenuto |
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Invited Paper -- Securely Optimized (Ethereum) Smart Contracts using Formal Methods -- Security and Resilience -- Attack Resilience Hyperproperties: Formal Security Analysis of (Automotive) Network Architectures under Active Compromise -- Reachability Analysis of Upper-Stack Manipulating Binary Code -- Resilience of Systems under Maximum Component Deviations -- Formal Specification and Verification 1 -- Axiomatisation of Solidity Memory and Storage -- ProbTest: Unit Testing for Probabilistic Programs -- Observable Semantics for Characterising Consistency Between Heterogeneous |
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Models -- Formal Specification and Verification 2 -- Certificates and Witnesses for Multi-objective ω-regular Queries in Markov Decision Processes -- On the Generation of Invalid Objects for Inferring More Precise Class Invariants -- A Rodin Plugin for Genera ng Proof Obliga ons for Invariant Preserva on for ASTDs -- Software Quality -- Detecting Memory Errors in Rust Programs Including Unsafe Foreign Code -- Are Users More Willing to Use Formally Verified Password Managers?- Can Large Language Models Help Students Prove Software Correctness? An Experimental Study with Dafny -- Artificial Intelligence and Formal Methods -- On the Comparison of Learned Classifiers -- Exploring Unknown Environments with UPPAAL STRATEGO: Safe Reinforcement Learning for Navigation and Pump Localization -- Specification-Guided Repair of Arithmetic Errors in Dafny Programs using LLMs. |
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Sommario/riassunto |
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This volume constitutes the proceedings of 23rd International Conference on Software Engineering and Formal Methods, SEFM 2025, held in Toledo, Spain, on November 10–14, 2025. The 13 full papers and 2 short papers included in this book were carefully reviewed and selected from 39 submissions. The proceedings also include 1 invited short paper. They were organized in topical sections as follows: security and resilience; formal specification and verification; software quality; and artificial intelligence and formal methods. |
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