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Kenneth A. Frank; Qinyun Lin; Spiro J. Maroulis – Grantee Submission, 2024
In the complex world of educational policy, causal inferences will be debated. As we review non-experimental designs in educational policy, we focus on how to clarify and focus the terms of debate. We begin by presenting the potential outcomes/counterfactual framework and then describe approximations to the counterfactual generated from the…
Descriptors: Causal Models, Statistical Inference, Observation, Educational Policy
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Neale, Dave – Oxford Review of Education, 2015
Recently, Stephen Gorard has outlined strong objections to the use of significance testing in social research. He has argued, first, that as the samples used in social research are almost always non-random it is not possible to use inferential statistical techniques and, second, that even if a truly random sample were achieved, the logic behind…
Descriptors: Statistical Significance, Statistical Analysis, Sampling, Probability
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Cooper, Barry; Glaesser, Judith – International Journal of Social Research Methodology, 2016
Ragin's Qualitative Comparative Analysis (QCA) is often used with small to medium samples where the researcher has good case knowledge. Employing it to analyse large survey datasets, without in-depth case knowledge, raises new challenges. We present ways of addressing these challenges. We first report a single QCA result from a configurational…
Descriptors: Social Science Research, Robustness (Statistics), Educational Sociology, Comparative Analysis
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Onwuegbuzie, Anthony J.; Collins, Kathleen M. T. – Qualitative Report, 2007
This paper provides a framework for developing sampling designs in mixed methods research. First, we present sampling schemes that have been associated with quantitative and qualitative research. Second, we discuss sample size considerations and provide sample size recommendations for each of the major research designs for quantitative and…
Descriptors: Social Science Research, Qualitative Research, Methods Research, Sample Size
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Yeaton, William H.; Sechrest, Lee – Evaluation Review, 1986
The central thesis of this article is that the process of eliminating validity threats depends fundamentally on no-difference findings, a fact that has not been made explicit by researchers. The implications of this neglect are explored using examples from a number of different substantive areas such as psychology, health, and medicine.…
Descriptors: Attrition (Research Studies), Construct Validity, Generalizability Theory, Hypothesis Testing