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This article analyzes the self-correction of spelling by learners of intermediate Japanese. Participants in this study consisted of 20 students with "kanji" (Chinese characters) background and 43 without. This study investigates (1) types of spelling errors made; (2) the success rate of corrections made when codes for types of errors (error-codes) were given; (3) strategies used for correcting spelling errors; (4) reasons for a failure to correct errors; and (5) measures for further improvement in correction rates. Three methods, including "think-aloud", observation notes, and the writing of an essay before and after corrections, were used as research tools. The findings show a high rate of success in the self-correction strategies. The errors made by the students may be attributed to a number of different causes. On the basis of the findings, this article puts forth the following suggestions, among others: the provision of increased time for corrections, of more detailed instruction in "kanji", and of correct pronunciation instruction; increased practice in the use of dictionaries; and improved codes to indicate types of errors. (Contains 5 tables.)

Focuses on error correction strategies employed by learners of Japanese when revising their written work. Investigates the effectiveness of the coding system employed by a university entrance assessment in Australia; types of code symbols that lead to successful self-correction; strategies used for self-correction; and successful and unsuccessful strategies employed for the investigation. (Author/VWL)

Background: Case-crossover studies have been widely used in various fields including pharmacoepidemiology. Vines and Farrington indicated in 2001 that when within-subject exposure dependency exists, conditional logistic regression can be biased. However, this bias has not been well studied.Methods: We have extended findings by Vines and Farrington to develop a weighting method for the case-crossover study which removes bias from within-subject exposure dependency. Our method calculates the exposure probability at the case period in the case-crossover study which is used to weight the likelihood formulae presented by Greenland in 1999. We simulated data for the population with a disease where most patients receive a cyclic treatment pattern with within-subject exposure dependency but no time trends while some patients stop and start treatment. Finally, the method was applied to real-world data from Japan to study the association between celecoxib and peripheral edema and to study the association between selective serotonin reuptake inhibitor (SSRI) and hip fracture in Australia.Results: When the simulated rate ratio of the outcome was 4.0 in a case-crossover study with no time-varying confounder, the proposed weighting method and the Mantel-Haenszel odds ratio reproduced the true rate ratio. When a time-varying confounder existed, the Mantel-Haenszel method was biased but the weighting method was not. When more than one control period was used, standard conditional logistic regression was biased either with or without time-varying confounding and the bias increased (up to 8.7) when the study period was extended. In real-world analysis with a binary exposure variable in Japan and Australia, the point estimate of the odds ratio (around 2.5 for the association between celecoxib and peripheral edema and around 1.6 between SSRI and hip fracture) by our weighting method was equal to the Mantel-Haenszel odds ratio and stable compared with standard conditional logistic regression.Conclusion: Case-crossover studies may be biased from within-subject exposure dependency, even without exposure time trends. This bias can be identified by comparing the odds ratio by the Mantel-Haenszel method and that by standard conditional logistic regression. We recommend using our proposed method which removes bias from within-subject exposure dependency and can account for time-varying confounders. [ABSTRACT FROM AUTHOR]

Biodiversity knowledge shortfalls, especially incomplete information on species distributions, can lead to false conclusions about global biodiversity patterns. Diversity estimation theory statistically uses species occurrence records and sampling completeness (coverage) to predict diversity in terms of species richness, dominance and evenness. We estimated Scleractinia coral species diversity at different spatial resolutions, based on 109,296 occurrences and range data for 697 species, using an incidence‐based Hill's numbers approach through a rarefaction and extrapolation technique. We found that spatial patterns of diversity estimates were dependent on a geographic scale. The latitudinal and longitudinal diversity gradients, particularly at finer spatial scales, differed from species range‐based coral biodiversity hotspots of previous studies. The western Indian Ocean was predicted to have the most coral species, with greater diversities than in the Indo‐Pacific Coral Triangle. We concluded that the identification of marine biodiversity hotspots is sensitive to species commission errors (from range maps) and biased sampling coverage. Moreover, estimates of the geographic distribution of species richness informed us of a set of priority areas (the northeastern coast of Australia, central Coral Triangle and coast of Madagascar) for future sampling of unknown coral species occurrence. Our findings of biogeographical survey priorities contribute to filling biodiversity shortfalls for tropical coral reefs through sampling completeness, and consequently for development of conservation planning. [ABSTRACT FROM AUTHOR]