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Journal Article 1: Syed, M. & Nelson, S. C. (2015). Guidelines for establishing reliability when coding narrative data. Emerging Adulthood, 3, 375–387.

Abstract: The use of quantitative, qualitative, and mixed methods approaches has been foundational to research on emerging adulthood, yet there remain many unresolved methodological issues pertaining to how to handle qualitative data. The purpose of this article is to review best practices for coding and establishing reliability when working with narrative data. In doing so, we highlight how establishing reliability must be seen as an evolving process, rather than simply a focus on the end product. The review is divided into three broad sections. In the first section, we discuss relatively more quantitatively focused methods of coding and establishing reliability, whereas in the second section we discuss relatively more qualitatively focused methods. In the final section, we provide recommendations for researchers interested in coding narrative and other types of open-ended data. This article is intended to serve as an essential resource for researchers working on a variety of topics related to emerging adulthood and beyond.

Journal Article 2: Cheung, H. K., Hebl, M., King, E. B., Markell, H., Markel, C., & Nittrouer, C. (2017). Back to the future: Methodologies that capture real people in the real world. Social Psychological and Personality Science, 8, 564–572.

Abstract: This article argues that social and personality psychology theory and findings have been unnecessarily hampered by our reliance on a set of methodological lenses that sacrifice external validity and generalizability. We further urge researchers to renew their use of both classic and evolving alternative methodologies. In particular, we discuss and consider pros and cons of field experiments, big data, archival research, and observations. We propose that it is up to us, as researchers, to ensure that we maximize the breadth of our theory and quality of data by expanding and triangulating the ways in which we collect data.