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Psychological constructs such as personality dimensions or cognitive traits are typically unobserved and are therefore measured by observing so-called indicators of the latent construct (e.g., responses to questionnaire items or observed behavior). The Common Factor Model (CFM) models the relations between the observed indicators and the latent variable. In this article we argue in favor of interpreting the CFM as a causal model rather than merely a statistical model, in which common factors are only descriptions of the indicators. When there is sufficient reason to hypothesize that the underlying causal structure of the data is a common cause structure, a causal interpretation of the CFM has several benefits over a merely statistical interpretation of the model. We argue that (1) a causal interpretation conforms with most research questions in which the goal is to explain the correlations between indicators rather than merely summarizing them; (2) a causal interpretation of the factor model legitimizes the focus on shared, rather than unique variance of the indicators; and (3) a causal interpretation of the factor model legitimizes the assumption of local independence.

Practice’ in The Cambridge Guide to Second Language Teacher Education. A. Burns and J. C. Richards (eds.), pp. 298-307. Cambridge: Cambridge University Press. Cosh, J. 1999. ‘Peer observation: a reflective model’ in ELT Journal. 53/1, pp. 22-27. Farrell, T.S.C. 2008. ‘Critical incidents in ELT initial teacher training’ in ELT Journal, 62/1, pp. 3-10. Fenton-Smith, B. & Stillwell, C. 2011. ‘Reading discussion groups for teachers: connecting theory to practice’ in ELT Journal. 65/3, pp. 251-259. Gun, B. 2011. ‘Quality self-reflection through reflection training’ in ELT

emotional intelligence have on medical students? Medical Teacher, 34(1), 11-19. Coakley, E., & Scoble, K. B. (2003). A reflective model for organizational assessment and interventions. The Journal of Nursing Administration, 33(12), 660-669. Corrigan, J., Eden, J., Smith, B. M., NetLibrary, I., & Institute of Medicine (U.S.) Committee on Enhancing Federal Healthcare Quality Programs. (2003). Leadership by example: Coordinating government roles in improving health care quality. Washington, D.C: National Academies Press. Czabanowska, K., Malho, A., Schröder-Bäck, P., Popa, D

variables. Evaluation of reflective model consists of indicator reliability, discriminant validity, internal consistency, and convergent validity. After evaluating the outer model, an inner model evaluation is performed. There are two basic evaluations at this stage, namely the t-test to examine the effect of latent variables on other latent variables. To see the magnitude of influence is to see the path coefficient. The coefficients of determination R2 is used to measure how much variation in latent dependent variables is explained by the independent. Table 2

providing patient-centered services for patients and improving the quality of service. 2 Methods A number of reflective models have been developed, making it easier for practitioners to reflect on practice, such as Gibbs’ Reflective Cycle, Kolb’s Experiential Learning Cycle, John’s Model of Structured Reflection, and Smyth’s reflective framework. In this article, Smyth’s reflective framework with four stages will be used to guide the author’s reflection process. Dewey 6 defined reflection as a specialized form of thinking, which has a directly relationship with the

advantages have been verified in numerous studies. In order to grasp the process of reflection and embrace the reflective skill, I reflect on a practice-based issue in relation to hegemony and power relationship between doctors and nurses in the workplace to gain new understanding and thus improve the my clinical practice. 2 Methods Although numerous useful reflective models have been developed in recent decades, Smyth’s framework 2 is one of the commonly utilized models in nursing practice, which helps to critique the status quo in power relationships and increases

distributions; it is more appropriate for exploration than confirmation ( S. Yang, Liu, & Wei, 2016 ); it is suitable when the sample size is relatively small. The theoretical model (shown in Figure 1 ) was analyzed using SmartPLS 3.0. 5.1 Outer Reflective Model Evaluation Consideration of formative and reflective outer model modes is important when using PLS-SEM because two approaches to measurement are based on different principles and therefore require different evaluation measures. In this study, the latent variables represent the common factor of several specific

consistency (the mO-S3) had lower estimates. These lower values of the mO-S3 might be explained by the method to calculate internal consistency which was used by Swift et al. (2013) . They calculated internal consistency with regard to a 6 station OSCE, with stations designed to measure competence in musculoskeletal physiotherapy. However, the content of the stations varied to some extent. This conflicts with the stance of Cortina (1993 ) who stated that when internal consistency is measured, the set of test items should form a reflective model, that is, ‘all items are a