Prevalence and characteristics of avoidant/restrictive food intake disorder in a cohort of young patients in day treatment for eating disorders.

Interactions between (multiple indicator) latent variables are rarely used because of implementation complexity and competing strategies. Based on 4 simulation studies, the traditional constrained approach performed more poorly than did 3 new approaches--unconstrained, generalized appended product indicator, and quasi-maximum-likelihood (QML). The authors' new unconstrained approach was easiest to apply. All 4 approaches were relatively unbiased for normally distributed indicators, but the constrained and QML approaches were more biased for nonnormal data; the size and direction of the bias varied with the distribution but not with the sample size. QML had more power, but this advantage was qualified by consistently higher Type I error rates. The authors also compared general strategies for defining product indicators to represent the latent interaction factor.

We evaluated whether "more is ever too much" for the number of indicators (p) per factor (p/f) in confirmatory factor analysis by varying sample size (N = 50-1000) and p/f (2-12 items per factor) in 35,000 Monte Carlo solutions. For all N's, solution behavior steadily improved (more proper solutions, more accurate parameter estimates, greater reliability) with increasing p/f. There was a compensatory relation between N and p/f: large p/f compensated for small N and large N compensated for small p/f, but large-N and large-p/f was best. A bias in the behavior of the χ(2) was also demonstrated where apparent goodness of fit declined with increasing p/f ratios even though approximating models were "true". Fit was similar for proper and improper solutions, as were parameter estimates form improper solutions not involving offending estimates. We also used the 12-p/f data to construct 2, 3, 4, or 6 parcels of items (e.g., two parcels of 6 items per factor, three parcels of 4 items per factor, etc.), but the 12-indicator (nonparceled) solutions were somewhat better behaved. At least for conditions in our simulation study, traditional "rules" implying fewer indicators should be used for smaller N may be inappropriate and researchers should consider using more indicators per factor that is evident in current practice.

Academically selective schools are intended to affect academic self-concept positively, but theoretical and empirical research demonstrates that the effects are negative. The big-fish-little-pond effect (BFLPE), an application of social comparison theory to educational settings, posits that a student will have a lower academic self-concept in an academically selective school than in a nonselective school. This study, the largest cross-cultural study of the BFLPE ever undertaken, tested theoretical predictions for nationally representative samples of approximately 4,000 15-year-olds from each of 26 countries (N = 103,558) who completed the same self-concept instrument and achievement tests. Consistent with the BFLPE, the effects of school-average achievement were negative in all 26 countries (M beta = -.20, SD = .08), demonstrating the BFLPE's cross-cultural generalizability.

The big-fish-little-pond effect (BFLPE) predicts that equally able students have lower academic self-concepts (ASCs) when attending schools where the average ability levels of classmates is high, and higher ASCs when attending schools where the schoolaverage ability is low. BFLPE findings are remarkably robust, generalizing over a wide variety of different individual student and contextual level characteristics, settings, countries, long-term follow-ups, and research designs. Because of the importance of ASC in predicting future achievement, coursework selection, and educational attainment, the results have important implications for the way in which schools are organized (e.g., tracking, ability grouping, academically selective schools, and gifted education programs). In response to Dai and Rinn (Educ. Psychol. Rev., 2008), we summarize the theoretical model underlying the BFLPE, minimal conditions for testing the BFLPE, support for its robust generalizability, its relation to social comparison theory, and recent research extending previous implications, demonstrating that the BFLPE stands up to scrutiny. Educ Psychol Rev (2008) 20:319-350 DOI 10.1007 Quotations (associated page numbers) to the Dai and Rinn (2008) article are based on a prepublication version of the article available to the authors of this article that may have changed during the final preparation for publication.The authors would also like to express thanks to David Dai and Anne Rinn for their encouragement and assistance to us in preparation of our article, whilst still acknowledging that they might not agree will all the views expressed here. Keywords Big-fish-little-pond-effect . Social comparison theory . Ability grouping . Academic self-concept In its simplest form, the big-fish-little-pond effect (BFLPE) predicts that students have lower academic self-concepts (ASC) when attending schools where the average ability levels of other students is high compared to equally able students attending schools where the school-average ability is low. Findings support the BFLPE and are remarkably robust, generalizing over a wide variety of different individual student and contextual level characteristics, settings, countries, longterm followups, and research designs. The results also have important policy implications for the ways in which schools are organized (e.g., ability grouping, tracking, selective schools, gifted education programs, etc.). An Advance OrganizerThe Dai and Rinn (2008) critique of the BFLPE is reminiscent in many ways of the Dai (2004) comment on a cross-cultural study on the BFLPE by Marsh and Hau (2003). To differing extents, both critiques by Dai (2004) and by Dai and Rinn (2008) suggested that: the BFLPE might be a short-term, ephemeral effect; noted situations in which there might be positive effects of school-average ability on ASC that is claimed to be inconsistent with BFLPE predictions; argued that there might be a number of individual student or contextual characteristics that moderate the BFLPE; contrasted BF...