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Hitchcock, John H.; Johnson, R. Burke; Schoonenboom, Judith – Research in the Schools, 2018
The central purpose of this article is to provide an overview of the many ways in which special educators can generate and think about causal inference to inform policy and practice. Consideration of causality across different lenses can be carried out by engaging in multiple method and mixed methods ways of thinking about inference. This article…
Descriptors: Causal Models, Statistical Inference, Special Education, Educational Research
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Roth, Wolff-Michael – Journal of Research in Science Teaching, 2011
In the wake of an increasing political commitment to evidence-based decision making and evidence-based educational reform that emerged with the No Child Left Behind effort, the question of what counts as evidence has become increasingly important in the field of science education. In current public discussions, academics, politicians, and other…
Descriptors: Science Education, Educational Research, Evidence, Definitions
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Zientek, Linda Reichwein; Ozel, Z. Ebrar Yetkiner; Ozel, Serkan; Allen, Jeff – Career and Technical Education Research, 2012
Confidence intervals (CIs) and effect sizes are essential to encourage meta-analytic thinking and to accumulate research findings. CIs provide a range of plausible values for population parameters with a degree of confidence that the parameter is in that particular interval. CIs also give information about how precise the estimates are. Comparison…
Descriptors: Vocational Education, Effect Size, Intervals, Self Esteem
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Killeen, Peter R. – Psychological Methods, 2010
Lecoutre, Lecoutre, and Poitevineau (2010) have provided sophisticated grounding for "p[subscript rep]." Computing it precisely appears, fortunately, no more difficult than doing so approximately. Their analysis will help move predictive inference into the mainstream. Iverson, Wagenmakers, and Lee (2010) have also validated…
Descriptors: Replication (Evaluation), Measurement Techniques, Research Design, Research Methodology