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von Hippel, Paul T. – Sociological Methods & Research, 2020
When using multiple imputation, users often want to know how many imputations they need. An old answer is that 2-10 imputations usually suffice, but this recommendation only addresses the efficiency of point estimates. You may need more imputations if, in addition to efficient point estimates, you also want standard error (SE) estimates that would…
Descriptors: Computation, Error of Measurement, Data Analysis, Children
Cheek, Kim A. – Research in Science Education, 2017
Ideas about temporal (and spatial) scale impact students' understanding across science disciplines. Learners have difficulty comprehending the long time periods associated with natural processes because they have no referent for the magnitudes involved. When people have a good "feel" for quantity, they estimate cardinal number magnitude…
Descriptors: Foreign Countries, Scientific Concepts, Science Education, Spatial Ability
Finch, W. Holmes – Journal of Experimental Education, 2016
Multivariate analysis of variance (MANOVA) is widely used in educational research to compare means on multiple dependent variables across groups. Researchers faced with the problem of missing data often use multiple imputation of values in place of the missing observations. This study compares the performance of 2 methods for combining p values in…
Descriptors: Multivariate Analysis, Educational Research, Error of Measurement, Research Problems
Pantelis, Peter C.; Kennedy, Daniel P. – Autism: The International Journal of Research and Practice, 2016
Two-phase designs in epidemiological studies of autism prevalence introduce methodological complications that can severely limit the precision of resulting estimates. If the assumptions used to derive the prevalence estimate are invalid or if the uncertainty surrounding these assumptions is not properly accounted for in the statistical inference…
Descriptors: Foreign Countries, Pervasive Developmental Disorders, Autism, Incidence
Mahon, Anthony D.; Marjerrison, Andrea D.; Lee, Jonah D.; Woodruff, Megan E.; Hanna, Lauren E. – Research Quarterly for Exercise and Sport, 2010
In this study, we compared measured maximal heart rate (HRmax) to two different HRmax prediction equations [220-age and 208-0.7(age)] in 52 children ages 7-17 years. We determined the relationship of chronological age, maturational age, and resting HR to measured HRmax and assessed seated resting HR and HRmax during a graded exercise test.…
Descriptors: Metabolism, Maturity (Individuals), Age, Prediction