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Stapleton, Laura M.; Kang, Yoonjeong – Sociological Methods & Research, 2018
This research empirically evaluates data sets from the National Center for Education Statistics (NCES) for design effects of ignoring the sampling design in weighted two-level analyses. Currently, researchers may ignore the sampling design beyond the levels that they model which might result in incorrect inferences regarding hypotheses due to…
Descriptors: Probability, Hierarchical Linear Modeling, Sampling, Inferences
Adolph, Karen E.; Robinson, Scott R. – Journal of Cognition and Development, 2011
Research in developmental psychology requires sampling at different time points. Accurate depictions of developmental change provide a foundation for further empirical studies and theories about developmental mechanisms. However, overreliance on widely spaced sampling intervals in cross-sectional and longitudinal designs threatens the validity of…
Descriptors: Intervals, Children, Sampling, Developmental Psychology
Xu, Fei; Tenenbaum, Joshua B. – Developmental Science, 2007
We report a new study testing our proposal that word learning may be best explained as an approximate form of Bayesian inference (Xu & Tenenbaum, in press). Children are capable of learning word meanings across a wide range of communicative contexts. In different contexts, learners may encounter different sampling processes generating the examples…
Descriptors: Semantics, Bayesian Statistics, Sampling, Inferences