SAGE Research Methods Cases
Bofah, E. & Hannula, M, (2014). Structural equation modelling: Testing for the factorial validity, replication and measurement invariance of students' views on mathematics. SAGE Research Methods Cases. 10.4135/978144627305014529518
In this study, we provide a detailed account of processes involved in applying structural equation modelling to validate a survey instrument – the students' view of mathematics instrument – in a new cultural setting. First, we tested the factorial validity of the instruments in Ghana for 12th-grade students (N = 2034, M = 18.49, standard deviation = 1.25; 58.2% girls). Second, in the event of model misfit, we proposed and tested an alternate factorial structure. Third, we cross-validated the new structure with an independent sample from the Ghanaian data set. Fourth, we evaluated the factorial invariance across students' gender. Initial reliability estimates and confirmatory factor analysis indicated that the data set does not fit the hypothesized model (seven-factors). Subsequent exploratory factor analysis indicated a four-factor structure for the data set. The study has important implications for studies using structural equation modelling to validate survey instruments and shows the methodological challenges associated with the importation of a Western survey instrument into a different cultural environment.
Kuip, M, (2017). The challenges of measuring moral distress in the context of social and health care. SAGE Research Methods Cases. 10.4135/9781526406729
Defining the experience of moral distress in all its complexity, and building a valid instrument to measure it, has presented a major challenge for researchers conducting surveys on this issue. The various and partially inadequate definitions of the concept have led to varying and sometimes even controversial ways of measuring it. This case study centers on the challenges that I faced when I was studying experiences of moral distress among professional social workers. The study is based on an empirical article aimed at shedding light on the experiences of moral distress among social workers with specific focus on the role of perceived resource insufficiencies in explaining these experiences. The empirical article utilized survey data collected as a part of my dissertation project on the capabilities and well-being of professional social workers.
In this case study, I focus in particular on the methodological and theoretical challenges presented by the conceptualization, operationalization, and measurement of this phenomenon. Here, moral distress is defined as work-related distress experienced by different professionals in the field of social and health care. It develops when a person is not able to practice in a way he or she considers morally appropriate, owing, for example, to personal, institutional, or organizational obstacles. It is measured with a binary construct consisting of two elements: one measuring the experience of moral distress, that is to say the restricted capability to practice in full accordance with one’s moral code; and the other the impaired well-being related to this incapability.
Oller, S, (2014). Exploratory factor analysis as a tool for investigating complex relationships: When numbers are preferred over descriptions and opinions. SAGE Research Methods Cases. 10.4135/978144627305014531373
Exploratory Factor analysis is a research tool that can be used to make sense of multiple variables which are thought to be related. This can be particularly useful when a qualitative methodology may be the more appropriate method for collecting data or measures, but quantitative analysis enables better reporting. This case first gives a brief overview of exploratory factor analysis and then follows with a case study employing it.
Cohen, A, (2014). Using a log-linear model to calculate risk ratios for social epidemiology analysis. SAGE Research Methods Cases. 10.4135/978144627305013520670
This case study presents an example of using a generalized linear model with a log-linear link to calculate an adjusted risk ratio to be able to assess the association between educational attainment and obesity in a cohort study of American adults. Both risk ratios and odds ratios can be calculated based on cohort study data, and risk ratios are more intuitive for practitioners to interpret. I present tips on how to estimate adjusted risk ratios, including a way to avoid non-convergence of the model. I then explain how to interpret risk ratios. In conclusion, generalized linear models with a log-linear link function can be a useful statistical analytic tool when a risk ratio is possible to calculate and is of greater interest than an odds ratio.
Ma, S., Rotherham, I. & Ma, S, (2014). Winning matches in tennis Grand Slam men's singles: A logistic model. SAGE Research Methods Cases. 10.4135/978144627305013516575
This study evaluates potential factors determining match wins in tennis Grand Slam men's singles. Previous studies used true experimental designs, quasi-experimental designs and questionnaire surveys with small sample sizes to capture the conditions in the events. However, they generally fall short of producing a comprehensive answer to the key research question. Our study used a large-scale sample of 9144 matches (including 845 players) in tennis men's singles Grand Slam tournaments from 1991 to 2008, retrieved from the official open-access website of the Association of Tennis Professionals. In particular, we sought to build a model that controls what we considered as all of the important factors. These factors included match characteristics (such as court surface), personal characteristics (such as stature and age) and skills (such as service and return) that can influence match outcomes. In this case study, we examine the particular challenges in collecting and managing secondary data, adopting appropriate statistical analysis methods and delivering accurate and in-depth data interpretation. It has shown exceptional value of using regression analysis methods in analysing repeated-measures nature of data. A fruitful line of this inquiry would benefit from the wider conclusions we drew.
Yu, H, (2017). Examining the relation between part-time faculty employment and student academic achievement using hierarchical linear modeling. SAGE Research Methods Cases. 10.4135/9781473972926
The increasing demand for access to higher education and declining financial support from states help fuel the increasing employment of part-time faculty at US institutions of higher education. Although prior studies acknowledged employing part-time faculty is positively associated with student learning or choice of major as they bring professional experience to their respective fields, the majority of studies suggest there is a negative association between part-time faculty appointment and student academic achievement. My research project further investigated such association using multilevel logistic regression and a nationally representative sample of college students from 2-year community colleges in the United States. This case study provides a succinct account of my 4-year research project, taking readers to the heart of some specific methodological challenges or problems that arose during this research process. It is my hope that this case study offers some useful suggestions and tips for students who aim to conduct statistical analysis using a similar methodological approach.
Russell, H., White, A. & Wiese-Bjornstal, D, (2017). Physical and psychological changes during marathon training and running injuries: An interdisciplinary, repeated-measures approach. SAGE Research Methods Cases. 10.4135/9781526420770
Marathon running is an increasingly popular form of physical activity. Despite its popularity, sport psychology research on marathon runners is limited, as are interdisciplinary approaches to evaluating performance results and health consequences of marathon training. Our Sports Medicine Psychology Laboratory research group partnered with exercise physiologists from the Sports Performance Laboratory 3 years ago to implement an ongoing interdisciplinary research program examining physical and psychological adaptations among approximately 100 novice runners taking a university-sponsored course in marathon training. Each year we have employed a repeated-measures design and made adaptations to the psychological constructs measured based on a specific overall purpose and focus for that year. We employed quantitative methods of analysis following the first and second years’ data collections to assess physical and psychological factors predicting sport injuries and psychological responses to injuries and in the third year to examine positive psychology constructs related to participation and performance. In this case study, we describe the methods of the sport psychology component of this marathon training study as well as the challenges and lessons learned while conducting this research.