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Brino, Ana Leda F., Barros, Romariz S., Galvao, Ol; Garotti, M.; Da Cruz, Ilara R. N.; Santos, Jose R.; Dube, William V.; McIlvane, William J. – Journal of the Experimental Analysis of Behavior, 2011
This paper reports use of sample stimulus control shaping procedures to teach arbitrary matching-to-sample to 2 capuchin monkeys ("Cebus apella"). The procedures started with identity matching-to-sample. During shaping, stimulus features of the sample were altered gradually, rendering samples and comparisons increasingly physically dissimilar. The…
Descriptors: Followup Studies, Computation, Teaching Methods, Sample Size
Luh, Wei-Ming; Guo, Jiin-Huarng – Journal of Experimental Education, 2009
The sample size determination is an important issue for planning research. However, limitations in size have seldom been discussed in the literature. Thus, how to allocate participants into different treatment groups to achieve the desired power is a practical issue that still needs to be addressed when one group size is fixed. The authors focused…
Descriptors: Sample Size, Research Methodology, Evaluation Methods, Simulation
Murphy, Daniel L.; Pituch, Keenan A. – Journal of Experimental Education, 2009
The authors examined the robustness of multilevel linear growth curve modeling to misspecification of an autoregressive moving average process. As previous research has shown (J. Ferron, R. Dailey, & Q. Yi, 2002; O. Kwok, S. G. West, & S. B. Green, 2007; S. Sivo, X. Fan, & L. Witta, 2005), estimates of the fixed effects were unbiased, and Type I…
Descriptors: Sample Size, Computation, Evaluation Methods, Longitudinal Studies
Yoo, Jin Eun – Educational and Psychological Measurement, 2009
This Monte Carlo study investigates the beneficiary effect of including auxiliary variables during estimation of confirmatory factor analysis models with multiple imputation. Specifically, it examines the influence of sample size, missing rates, missingness mechanism combinations, missingness types (linear or convex), and the absence or presence…
Descriptors: Monte Carlo Methods, Research Methodology, Test Validity, Factor Analysis

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