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York, Richard – International Journal of Social Research Methodology, 2018
A common motivation for adding control variables to statistical models is to reduce the potential for spurious findings when analyzing non-experimental data and to thereby allow for more reliable causal inferences. However, as I show here, unless "all" potential confounding factors are included in an analysis (which is unlikely to be…
Descriptors: Inferences, Control Groups, Correlation, Experimental Groups
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Theobald, Elli – CBE - Life Sciences Education, 2018
Discipline-based education researchers have a natural laboratory--classrooms, programs, colleges, and universities. Studies that administer treatments to multiple sections, in multiple years, or at multiple institutions are particularly compelling for two reasons: first, the sample sizes increase, and second, the implementation of the treatments…
Descriptors: Educational Research, Hierarchical Linear Modeling, Program Implementation, Predictor Variables
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What Works Clearinghouse, 2014
Attrition occurs when members of the initial research sample are not part of the final analysis sample, such as due to missing data or leaving the study. Both the overall sample attrition and the differences in attrition between the groups can affect the statistical equivalence of the sample and create potential for bias. The WWC has given careful…
Descriptors: Attrition (Research Studies), Statistical Bias, Randomized Controlled Trials, Models
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What Works Clearinghouse, 2013
Attrition occurs when members of the initial research sample are not part of the final analysis sample, such as due to missing data or leaving the study. Both the overall sample attrition and the differences in attrition between the groups can affect the statistical equivalence of the sample and create potential for bias. The WWC has given careful…
Descriptors: Attrition (Research Studies), Statistical Bias, Randomized Controlled Trials, Models