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Human subject research for engineers : a practical guide /
This Brief introduces engineers to the main principles in ethics, research design, statistics, and publishing of human subject research. In recent years, engineering has become strongly connected to disciplines such as biology, medicine, and psychology. Often, engineers (and engineering students) ar...
| Clasificación: | Libro Electrónico |
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| Autores principales: | , |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Cham :
Springer,
2017.
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| Colección: | SpringerBriefs in applied sciences and technology.
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| Temas: | |
| Acceso en línea: | Texto completo |
Tabla de Contenidos:
- Preface; Who This Book Is For; Why This Book Is Important; Who This Book Is Not For; Scripts; References; Contents; 1 Scientific Method, Human Research Ethics, and Biosafety/Biosecurity; Abstract; 1.1 How Is Human Subject Research Different from Engineering?; 1.2 Hypothesis; 1.3 Is a Hypothesis Always Needed?; 1.4 Ethics; 1.4.1 Informed Consent; 1.4.2 Ethically Challenging Research Aspects; 1.4.3 Big Data Research; 1.4.4 Is Ethically Challenging Research Impossible?; 1.4.5 Isn't This Just Excessive Paperwork?; 1.5 Biosafety and Biosecurity; 1.5.1 Biosafety; 1.5.2 Biosecurity; References.
- 2 Experimental DesignAbstract; 2.1 Experiments and Quasi-experiments; 2.2 Between-Subjects Design; 2.2.1 Control Groups; 2.2.2 Participant Assignment to Groups; 2.3 Within-Subject Design; 2.4 Choosing Between-Subjects or Within-Subject Design: More Than just a Matter of Statistical Power; 2.5 Validity Threats in Experiments; 2.5.1 Demand Characteristics; 2.5.2 Experimenter Expectancy Effect; 2.6 Quasi-experiments; 2.7 Validity Threat in Quasi-experiments: Causation Versus Correlation; 2.8 Validity Threats in Experiments and Quasi-experiments; 2.8.1 Sample Representativeness; 2.8.2 Attrition.
- 2.9 Measurements and Measures2.9.1 Statistical Reliability; 2.9.2 Self-reported Measures (Questionnaires); 2.10 Finally, Some Tips Before Starting the Experiment; References; 3 Statistics; Abstract; 3.1 What This Chapter Does (Not) Cover; 3.2 Descriptive Statistics; 3.2.1 Central Tendency and Variability; 3.2.2 Effect Sizes; 3.2.2.1 Cohen's d; 3.2.2.2 Pearson Product-Moment Correlation Coefficient; 3.2.2.3 Point-Biserial Correlation; 3.2.2.4 Spearman Rank-Order Correlation; 3.2.2.5 Risk Ratios and Odds Ratios; 3.2.3 What is a Strong Effect?; 3.2.4 Why Tables Are Not Enough.
- 3.3 Inferential Statistics3.3.1 Sample Versus Population; 3.3.2 Hypothesis Testing; 3.3.3 Independent-Samples t Test; 3.3.4 Paired-Samples t Test; 3.3.5 One-Tailed Versus Two-Tailed Tests; 3.3.6 Alternatives to the t Test; 3.3.7 Multivariate Statistics; 3.4 Pitfalls of Null Hypothesis Significance Testing; 3.4.1 Most Published Research Findings Are False; 3.4.2 Bias; 3.4.3 Recommendations in Order to Maximize the Replicability of a Work; 3.5 Final Note; References; 4 Publishing; Abstract; 4.1 What Is Publishing and Why Is It Important?; 4.2 What Is a Research Paper?
- 4.2.1 Structure of a Research Paper4.2.1.1 Title; 4.2.1.2 Authorship; 4.2.1.3 Affiliations; 4.2.1.4 Abstract; 4.2.1.5 Main Text; 4.2.1.6 Acknowledgments, Disclosures, and Biographies; 4.2.1.7 References; 4.2.1.8 Supplementary Material; 4.2.1.9 Figures and Tables; 4.2.2 Writing Style; 4.2.3 Preventing Plagiarism; 4.2.4 Copyright; 4.2.5 Fraud; 4.3 Publication Bias; 4.4 The Process from Submission to Publishing; 4.5 Open Access Journals; 4.6 Scientometrics; 4.6.1 Impact Factor; 4.6.2 h-Index; 4.6.3 Altmetrics; References; MATLAB Scripts.