A cautionary note on the effects of range restriction on predictor intercorrelations.

The purpose of this research report is to highlight a unique set of issues that arise when considering the effects of range restriction in the context of estimating predictor intercorrelations. Three approaches are used to illustrate the issue: simulation, a concrete applied example, and a reanalysis of a meta-analysis of ability-interview correlations. The general conclusion is that a predictor intercorrelation can differ dramatically from the population value when both predictors are used in a composite that is used operationally for selection. The compensatory nature of a composite means that low scorers on one predictor can only obtain high scores on the composite if they obtain very high scores on the other predictor; this phenomenon distorts the correlation between the predictors. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Predicting group-level outcome variables from variables measured at the individual level: A latent variable multilevel model.

In multilevel modeling, one often distinguishes between macro-micro and micro-macro situations. In a macro-micro multilevel situation, a dependent variable measured at the lower level is predicted or explained by variables measured at that lower or a higher level. In a micro-macro multilevel situation, a dependent variable defined at the higher group level is predicted or explained on the basis of independent variables measured at the lower individual level. Up until now, multilevel methodology has mainly focused on macro-micro multilevel situations. In this article, a latent variable model is proposed for analyzing data from micro-macro situations. It is shown that regression analyses carried out at the aggregated level result in biased parameter estimates. A method that uses the best linear unbiased predictors of the group means is shown to yield unbiased estimates of the parameters. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Identifying criterion-related patterns of predictor scores using multiple regression.

Along with examples involving vocational interests and mathematics achievement, the authors describe a multiple regression based, pattern recognition procedure that can be used to identify a pattern of predictor scores associated with high scores on a criterion variable. This pattern is called the criterion pattern. After the criterion pattern has been identified, a second regression procedure can be used to estimate the proportion of variation attributable to the criterion pattern. Cross-validation can then be used to estimate the variation attributable to a criterion pattern derived from regression weights estimated in another sample. Finally, issues of criterion pattern invariance and interpretation are discussed. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

A Family Member's Job Loss as a Risk Factor for Smoking Among Adolescents.

Life events are associated with an increased likelihood of adolescent smoking. This study examined a family member's job loss as a predictor of smoking initiation over a 1-year period. Southern California students completed surveys in 6th and 7th grade. Of the 2,168 students, 252 (12%) reported that an adult in the household had lost a job within the past 6 months. Controlling for demographic, socioeconomic. educational, and parenting characteristics. 6th-grade never-smokers who reported a job loss were significantly more likely to have tried smoking by 7th grade and to have smoked in the past 30 days. Job loss for a household member is a risk factor for adolescents' involvement in problem behaviors such as smoking. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Prediction of railway power demand

The short-term prediction problem is considered for power demand at railway energy supply stations of the Dutch national railway company. A model and an adaptive prediction algorithm are presented. The algorithm is based on a self-tuning predictor for the output of a Gaussian system.     

Validity and factor analyses of naval air training predictor and criterion measurers.

"The most substantial relationships existed between tests of academic aptitude and grades in the pre-flight phase of training. Tests of spatial and perceptual abilities correlated highest with final basic and advanced flight grades. Four significant factors derived by factor analysis were: perceptual, academic potential, comprehension of relationships, and applied spatial relations [these factors, however, accounted for only 51 percent of the total variance]. Although the inclusion of criterion variables did not reveal any new factors, it did aid considerably in defining those factors found." 15 references. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Identification and prediction of two training criterion factors.

12 examination scores from 6 courses given as part of the Naval Pre-Flight Training Program were factored into two interpretable criterion factors. The intercorrelations of 10 predictor (standard test) variables were then added to the correlation matrix, and loadings for them on the criterion factors were obtained. Using the factor loadings of the predictors as validity coefficients, regression weights were found for them on each of the two criterion factors, using a modified Doolittle method. "The principal advantage… derived from the initial factor analysis of the criterion variables is that the obtained criterion factors may be isolated free from the influence of the variance of the predictor variables." (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

基于混沌系统模型的非线性语音预测器

语音信号的产生过程是非线性的,而且具有混沌性。相对于线性模型,在重构相空间中建立的语音信号模型更接近实际系统,神经网络是建立非线性系统模型的常用工具。实验结果表明：在重构相空间中建立的基于径向基函数神经网络的预测器较线性预测器在性能上有明显提高。     

动态规划算法在运动点目标检测中的应用研究

序列图像中低信噪比运动点目标的实时检测算法,是许多实时处理系统中的关键算法之一。该文在对面临的实际问题与对检测算法分析的基础上,详细阐述和研究了利用LS线性预测器的动态规划能量累积算法,并根据仿真实验的效果,指出此算法较直接动态规划能量累积算法可最大程度地降低能量扩散,减少团聚在目标周围的虚警目标点,十分利于后续轨迹关联检测处理.     

An approach for determination of asphaltene crystallite by X-ray diffraction analysis: A case of study

Asphaltenes were precipitated from atmospheric residue and divided into two fractions. One of them was left as such and the second one was submitted to washing under reflux. Characterization of both fractions was carried out through elemental analysis and X-ray diffraction. Diffractograms were analyzed in order to obtain crystallite parameters by smoothing processes previous to deconvolution and then local maxima of a polynomial function were detected. Major peaks were found at around 20°, 25°, and 41° corresponding to γ, (002) and (10) bands. Bragg and Scherrer equations were used to determine the aromatic interlayer and aliphatic distances, as well as thickness and diameter of aromatic sheets. The full-width at half-maximum (FWHM) of the main peaks was firstly estimated using the corrector formula, and therefore the corrector procedure was applied to improve the initial guesses of FWHM. Differences in crystallite parameters between both analyzed samples were observed when using this mathematical approach.