UC Santa Cruz

Quantitative researchers increasingly draw on ethnographic research that may not be generalizable to inform and interpret results from statistical analyses; at the same time, while generalizability is not always an ethnographic research goal, the integration of quantitative data by ethnographic researchers to buttress findings on processes and mechanisms has also become common. Despite the burgeoning use of dual designs in research, there has been little empirical assessment of whether the themes, narratives, and ideal types derived from qualitative fieldwork are broadly generalizable in a manner consistent with estimates obtained from quantitative analyses. We draw on simulated and real-world data to assess the bias associated with failing to align samples across qualitative and quantitative methodologies. Our findings demonstrate that significant bias exists in mixed-methods studies when sampling is incongruent within research designs. We propose three solutions to limit bias in mixed-methods research.