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Ibrahima Dina Diatta; André Berchtold – International Journal of Social Research Methodology, 2023
Using secondary data has many advantages, but there are also many limitations, including the lack of relevant information. This article draws on a previous study that used secondary data to investigate substance use in young, elite athletes. Three types of missing data appeared: missing data, lack of information about the data collection process,…
Descriptors: Data Analysis, Research Problems, Data Collection, Scientific Research
Bergeron, Dave A.; Gaboury, Isabelle – International Journal of Social Research Methodology, 2020
Realist evaluation (RE) is a research design increasingly used in program evaluation, that aims to explore and understand the influence of context and underlying mechanisms on intervention or program outcomes. Several methodological challenges, however, are associated with this approach. This article summarizes RE key principles and examines some…
Descriptors: Research Design, Program Evaluation, Context Effect, Research Problems
Corple, Danielle J.; Linabary, Jasmine R. – International Journal of Social Research Methodology, 2020
Many ethical concerns in online big data research stem from a pervasive assumption that data are disembodied and place-less. While some scholars have begun addressing the ethical dilemmas of big data, few offer approaches or tools that fully grapple with the situatedness of online data and its ethical implications. We draw on feminist new…
Descriptors: Feminism, Ethics, Research, Epistemology
Jack Denham; Matthew Spokes – International Journal of Social Research Methodology, 2023
In this paper we make a case for 'Little Data', which is real-time, self-collected, idiosyncratic datasets maintained by individuals about themselves on myriad topics. We develop and offer a methodology for combining these messy, highly personal insights, to make deductive observations about collective practices. In testing this approach, we use…
Descriptors: Research Problems, Data Analysis, Logical Thinking, Case Studies
Berchtold, André – International Journal of Social Research Methodology, 2019
Most quantitative studies in the social sciences suffer from missing data. However, despite the large availability of documents and software to treat such data, it appears that many social scientists do not apply good practices regarding missing data. We analyzed quantitative papers published in 2017 in six top-level social science journals.…
Descriptors: Research Problems, Research Methodology, Social Science Research, Data Analysis
Lee, Katherine J.; Roberts, Gehan; Doyle, Lex W.; Anderson, Peter J.; Carlin, John B. – International Journal of Social Research Methodology, 2016
Multiple imputation (MI), a two-stage process whereby missing data are imputed multiple times and the resulting estimates of the parameter(s) of interest are combined across the completed datasets, is becoming increasingly popular for handling missing data. However, MI can result in biased inference if not carried out appropriately or if the…
Descriptors: Data Analysis, Statistical Inference, Computation, Research Problems