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Abstract Background Gender bias within medical education is gaining increasing attention. However, valid and reliable measures are needed to adequately address and monitor this issue. This research conducts a psychometric evaluation of a short multidimensional scale that assesses medical students' awareness of gender bias, beliefs that gender bias should be addressed, and experience of gender bias during medical education. Methods Using students from the University of Wollongong, one pilot study and two empirical studies were conducted. The pilot study was used to scope the domain space ( n = 28). This initial measure was extended to develop the Gender Bias in Medical Education Scale (GBMES). For Study 1 ( n = 172), confirmatory factor analysis assessed the construct validity of the three-factor structure (awareness, beliefs, experience) and enabled deletion of redundant items. Study 2 ( n = 457) tested the generalizability of the refined scale to a new sample. Combining Study 1 and 2, invariance testing for program of study and gender was explored. The relationship of the GBMES to demographic and gender politics variables was tested. The results were analyzed in R using confirmatory factor analysis and Multiple-Indicator-Multiple-Indicator-Cause models. Results After analysis of the responses from the original 16-item GBMES (Study 1), a shortened measure of ten items fitted the data well (RMSEA = .063; CFI = .965; TLI = .951; Mean R-square of items = 58.6 %; reliability: .720–.910) and was found to generalize to a new sample in Study 2 (RMSEA = .068; CFI = .952; TLI = .933; Mean R-square of items = 55.9 %; reliability: .711–.892). The GBMES was found to be invariant across studies, gender, and program of study. Female students and those who supported gender equality had greater agreement for each of the factors. Likewise, postgraduate students reported higher scores on experience of gender bias than undergraduate students. Conclusion The GBMES provides a validated short multidimensional measure for use in research and policy. Given its good reliability across different target populations and its concise length, the GBMES has much potential for application in research and education to assess students' attitudes towards gender bias.

Leadership, management and entrepreneurship where -- Rethinking leadership -- Rethinking leadership development -- Coaching, psychometrics and 360 degree feedback -- Forum theatre -- Experiential exercises, simulations and (live) case studies -- Action learning sets -- Reflections -- Index

The RAND Online Measure Repository is an online searchable database of 171 measures of psychological health and traumatic brain injury, including measure domains, uses, psychometrics, and costs, that can be used to support program evaluation.

Introduction -- 1. Interview with James O. Ramsay -- 2. Interview with Peter M. Bentler -- 3. Interview with Lawrence J. Hubert -- 4. Interview with Jan de Leeuw -- 5. Interview with Bengt O. Muthen -- 6. Interview with Paul W. Holland -- 7. Interview with Robert Mislevy -- 8. Interview with Ivo Molenaar -- 9. Interview with Susan Embretson -- 10. Interview with Wim J. van der Linden -- 11. Interview with David M. Thissen -- 12. Interview with Bill Stout -- 13. Interview with Jacqueline J. Meulman -- 14. Interview with Willem J. Heiser -- 15. Interview with Ulf Böckenholt -- 16. Interview with Paul de Boeck -- 17. Interview with Brian Junker -- 18. Interview with Jos ten Berge -- 19. Interview with Klaas Sijtsma -- 20. Interview with Hua-Hua Chang.-Themes & Visions.

Intro -- Series Editors' Preface for David Torres Irribarra A Pragmatic Perspective of Measurement -- Mathematical Thinking, Social Practices, and the Locus of Science in Psychology -- References -- Preface -- Contents -- 1 Introduction -- 1.1 What Is Pragmatism? -- 1.2 A Brief Overview of Some Pragmatist Ideas -- 1.2.1 The Primacy of Practice -- 1.2.2 Fallibilism and Anti-skepticism -- 1.2.3 Historical and Social Nature of Knowledge -- 1.2.4 Abandoning Representationalism -- 1.2.5 Theories as Tools -- 1.2.5.1 Pragmatism Recapped -- 2 What Is Measurement? -- 2.1 Classical Theory of Measurement -- 2.2 Operationalism -- 2.3 The Representational Theory of Measurement -- 2.3.1 Campbell: Between the Classical and Representational Theories -- 2.3.2 Stevens: Between the Representational and Operationalist Theories -- 2.3.3 Axiomatic Measurement Theory -- 2.4 Latent Variable Modeling -- 2.5 Metrology -- 2.6 Defining Measurement? -- 3 Measurement: Prototypes and Resemblances -- 3.1 The Many Faces of Measurement -- 3.2 Protypes and Resemblances -- 3.3 Prototypical Measurement Practices -- 4 A Pragmatic Perspective of Measurement -- 4.1 Why an Activity? Why Three of Them? -- 4.2 Why According to a Model? -- 4.3 Why a ``relevant'' Attribute? -- 4.4 Why in Service of a Larger Goal? -- 5 Contrasting and Comparing -- 5.1 The Goals of Measurement -- 5.2 The Activities of Measurement -- 5.3 The Attributes We Measure -- 5.4 The Model of the Attribute -- 5.5 Summary -- References -- Index.

"This accessible textbook is for those without a mathematical background (just some notions of basic algebra are sufficient) and provides a comprehensive introduction to all topics covered in introductory behavioural science statistics courses. It includes plenty of real examples to demonstrate approaches in depth based on real psychology experiments utilizing the statistical techniques described. New content in this thoroughly updated second edition includes an introduction to Bayesian statistics which complements the coverage of Classical/Frequent statistics present in the first edition. It also offers practical details on how to perform analyses using JASP - a globally employed, freely downloadable statistical package. The updated Companion Website also features a range of new material including additional exercises so readers can test themselves on what they have learned in the book. This timely and highly readable text will be invaluable to undergraduate students of psychology and research methods courses in related disciplines, as well as anyone with an interest in understanding and applying the basic concepts and inferential techniques associated with statistics in the behavioural sciences"--

Intro -- Preface -- Contents -- About the Authors -- Chapter 1: Current Conceptualizations of Dynamic Risk Factors -- 1.1 Origins of DRF -- 1.2 Prediction -- 1.3 Treatment -- 1.4 Explanation -- 1.5 Theories of Sexual Offending -- 1.6 Recent Theoretical Developments: Agency -- 1.7 Causal Mechanisms -- 1.8 Summary -- References -- Chapter 2: Critical Analysis of Dynamic Risk Factors -- 2.1 Conceptual/Theoretical Problems -- 2.2 The Measurement of DRF and Change -- 2.3 Summary -- References -- Chapter 3: Reformulating Dynamic Risk Factors -- 3.1 Classification -- 3.2 Causal Criteria -- 3.3 Agency Approaches -- 3.4 Suggestions for Theory Development -- 3.5 DRF as Boundary Objects -- 3.6 Summary: Reformulating DRF -- References -- Chapter 4: Reformulating Dynamic Risk Factors and Practice Implications -- 4.1 Risk-Causality Method -- 4.2 Implications: Rehabilitation Theories -- 4.3 The Risk-Need-Responsivity Model -- 4.4 The Good Lives Model -- 4.5 Reformulated DRF and Case Formulation -- 4.6 Practical Implications of Reformulating DRF -- 4.7 Summary: Reformulating DRF and Practice Implications -- References -- Chapter 5: Conclusions and Future Directions -- 5.1 Future Directions -- 5.2 Final Conclusions -- References.

Measurement Instruments in Clinical Ethics presents an overview of studies of ethical concepts in clinical and research activities. The studies covered use interview scales or other methods of gathering data that have undergone rigorous analysis of their psychometric characteristics. This book describes these instruments and critiques their stage of development. This work strives to further the debate regarding what evolving ethical standards mean for clinicians and researchers.