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Can culture be a salient predictor of test-taking engagement? An analysis of differential noneffortful responding on an international college-level assessment of critical thinking.

a b s t r a c tA local Whittle estimator is developed to simultaneously estimate the long memory parameters for stationary anisotropic scalar random fields. It is shown that these estimators are consistent and asymptotically normal, under some weak technical conditions. A brief simulation study illustrates a practical application of the estimator.

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This study uses historical data to explore the consistency of SAT ® I: Reasoning Test score conversions and to examine trends in scaled score means. During the period from April 1995 to December 2003, both Verbal (V) and Math (M) means display substantial seasonality, and a slight increasing trend for both is observed. SAT Math means increase more than SAT Verbal means. Several statistical indices indicate that, during the period under study, raw-to-scale conversions are very stable, although conversions for extreme raw score points are less stable than are other conversions.

The goal of this study is to model pauses extracted from writing keystroke logs as a way of characterizing the processes students use in essay composition. Low-level timing data were modeled, the interkey interval and its subtype, the intraword duration, thought to reflect processes associated with keyboarding skills and composition fluency. Heavy-tailed probability distributions (lognormal and stable distributions) were fit to individual students' data. Both density functions fit reasonably well, and estimated parameters were found to be robust across prompts designed to assess student proficiency for the same writing purpose. In addition, estimated parameters for both density functions were statistically significantly associated with human essay scores after accounting for total time spent writing the essay, a result consistent with cognitive theory on the role of low-level processes in writing.

This paper discusses asymptotic distributions of various estimators of the underlying parameters in some regression models with long memory (LM) Gaussian design and nonparametric heteroscedastic LM moving average errors. In the simple linear regression model, the first-order asymptotic distribution of the least square estimator of the slope parameter is observed to be degenerate. However, in the second order, this estimator is n 1/2 -consistent and asymptotically normal for h + H < 3/2; nonnormal otherwise, where h and H are LM parameters of design and error processes, respectively. The finite-dimensional asymptotic distributions of a class of kernel type estimators of the conditional variance function σ 2 (x) in a more general heteroscedastic regression model are found to be normal whenever H < (1 + h)/2, and non-normal otherwise. In addition, in this general model, log(n)-consistency of the local Whittle estimator of H based on pseudo residuals and consistency of a cross validation type estimator of σ 2 (x) are established. All of these findings are then used to propose a lack-of-fit test of a parametric regression model, with an application to some currency exchange rate data which exhibit LM.