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Amaya, Ashley; Zimmer, Stephanie; Morton, Katherine; Harter, Rachel – Sociological Methods & Research, 2021
Address-based sampling (ABS) refers to the use a list of addresses derived from the U.S. Postal Service's Computerized Delivery Sequence File as a sampling frame. While most residential addresses are included on an ABS frame, it still suffers from undercoverage. Undercoverage is problematic only if the uncovered units have different attributes…
Descriptors: Sampling, Research Problems, Bias, Surveys
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Rudloff, Peter; Vinson, Laura Thaut – Sociological Methods & Research, 2023
This article details the challenges we faced in collecting sensitive information in an ethnically and religiously divided community that has experienced recent violence. The discussion is based on a summer 2016 survey experiment we conducted in Jos, Nigeria, to gather information regarding residents' perceptions of local communal violence. We…
Descriptors: Ethnicity, Conflict, Violence, Foreign Countries
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Møller, Jørgen; Skaaning, Svend-Erik – Sociological Methods & Research, 2021
The historical turn in social science has prompted scholars to engage with the work of historians on a large scale. Here, social scientists face two standard problems of selection bias: confirmation bias and convenience sampling. So far, the record of dealing with these problems has been poor, and little has been done to specify how social…
Descriptors: Historians, Bias, Sampling, Research Problems
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Su, Dan; Steiner, Peter M. – Sociological Methods & Research, 2020
Factorial surveys use a population of vignettes to elicit respondents' attitudes or beliefs about different hypothetical scenarios. However, the vignette population is frequently too large to be assessed by each respondent. Experimental designs such as randomized block confounded factorial (RBCF) designs, D-optimal designs, or random sampling…
Descriptors: Surveys, Vignettes, Factor Analysis, Research Design
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Tarray, Tanveer A.; Singh, Housila P.; Yan, Zaizai – Sociological Methods & Research, 2017
This article addresses the problem of estimating the proportion Pi[subscript S] of the population belonging to a sensitive group using optional randomized response technique in stratified sampling based on Mangat model that has proportional and Neyman allocation and larger gain in efficiency. Numerically, it is found that the suggested model is…
Descriptors: Models, Efficiency, Sampling, Research Problems