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Gelman, Andrew; Imbens, Guido – National Bureau of Economic Research, 2014
It is common in regression discontinuity analysis to control for high order (third, fourth, or higher) polynomials of the forcing variable. We argue that estimators for causal effects based on such methods can be misleading, and we recommend researchers do not use them, and instead use estimators based on local linear or quadratic polynomials or…
Descriptors: Regression (Statistics), Mathematical Models, Causal Models, Research Methodology
Kish, Leslie – 1989
A brief, practical overview of "design effects" (DEFFs) is presented for users of the results of sample surveys. The overview is intended to help such users to determine how and when to use DEFFs and to compute them correctly. DEFFs are needed only for inferential statistics, not for descriptive statistics. When the selections for…
Descriptors: Computer Software, Error of Measurement, Mathematical Models, Research Design
Mislevy, Robert J. – 1985
A method for drawing inferences from complex samples is based on Rubin's approach to missing data in survey research. Standard procedures for drawing such inferences do not apply when the variables of interest are not observed directly, but must be inferred from secondary random variables which depend on the variables of interest stochastically.…
Descriptors: Algorithms, Data Interpretation, Estimation (Mathematics), Latent Trait Theory
Sandler, Andrew B. – 1987
Statistical significance is misused in educational and psychological research when it is applied as a method to establish the reliability of research results. Other techniques have been developed which can be correctly utilized to establish the generalizability of findings. Methods that do provide such estimates are known as invariance or…
Descriptors: Analysis of Covariance, Analysis of Variance, Correlation, Discriminant Analysis