颅脑肿瘤切除术后硬膜外血肿的原因及预防

浅析颅脑肿瘤切除术后硬膜外血肿形成的原因及预防措施。回顾性分析本科室自2005年7月～2009年7月共计13例脑肿瘤术后硬膜外血肿发生的特点,所有病例血肿均发生于小脑幕上,其中7例位于额部,3例位于颞部,2例位于顶部,1例位于枕部;平均血肿量为(37.3±3.2)ml。脑肿瘤切除术后硬膜外血肿形成机制为多种原因所导致的颅内压及脑脊液动力学改变致硬脑膜与颅骨剥离有关。各环节采取相应预防措施及术后常规复查头颅CT是防治脑肿瘤术后非手术区域硬膜外血肿的关键。     

Response patterns of young children from two contrasting SES contexts to different numerical tasks with numbers 1–5

This study contributes to a multifaceted picture of young children’s emergent number knowledge by focusing on the variety of ways in which children express and use quantitative information. The authors’ aims are to (a) explore the extent to which quantifying collections 1–5 and using that information pose different levels of difficulty to children from 33 to 47?months old, (b) identify intra- and intertask response patterns, and (c) analyze the influence of socioeconomic status and age on these response patterns. Sixty-six children from two contrasting socioeconomic status groups (very low and middle) were asked to solve tasks with 1–5 elements in the context of a game. Using quantitative information turned out to be more complex than quantification. Intra- and intertask response patterns showed that children gradually come to understand the first five numerical values according to the numerical sequence in a much less strict way than that proposed by the cardinal-knowers model that posits that children progress in an orderly way in their number knowledge. Children in different ages and socioeconomic status groups were found to be more similar to each other when the whole arc of responses provided was considered than when solely correct performance was measured.     

耳标在小屏幕界面设计中的应用

耳标是一种向用户提供计算机客体、操作或交互信息的非言语听觉信号。本文比较了言语听觉界面与非言语听觉界面的特点 ,并就非言语听觉界面设计中的两种基本表征方式———耳标技术和听标技术的优缺点做了简单介绍 ,指出耳标技术是用于小屏幕界面设计的有效方式之一。作者重点概述了耳标的构成元素、构成方式以及信息呈现方式 ,并从功效学角度对耳标设计原则作了简要总结     

The Performance of Multivariate Methods for Two-Group Comparisons with Small Samples and Incomplete Data

Abstract

In intervention studies having multiple outcomes, researchers often use a series of univariate tests (e.g., ANOVAs) to assess group mean differences. Previous research found that this approach properly controls Type I error and generally provides greater power compared to MANOVA, especially under realistic effect size and correlation combinations. However, when group differences are assessed for a specific outcome, these procedures are strictly univariate and do not consider the outcome correlations, which may be problematic with missing outcome data. Linear mixed or multivariate multilevel models (MVMMs), implemented with maximum likelihood estimation, present an alternative analysis option where outcome correlations are taken into account when specific group mean differences are estimated. In this study, we use simulation methods to compare the performance of separate independent samples t tests estimated with ordinary least squares and analogous t tests from MVMMs to assess two-group mean differences with multiple outcomes under small sample and missingness conditions. Study results indicated that a MVMM implemented with restricted maximum likelihood estimation combined with the Kenward–Roger correction had the best performance. Therefore, for intervention studies with small N and normally distributed multivariate outcomes, the Kenward–Roger procedure is recommended over traditional methods and conventional MVMM analyses, particularly with incomplete data.     

Testing Differential Item Functioning in Small Samples

Abstract

Differential item functioning (DIF) is a pernicious statistical issue that can mask true group differences on a target latent construct. A considerable amount of research has focused on evaluating methods for testing DIF, such as using likelihood ratio tests in item response theory (IRT). Most of this research has focused on the asymptotic properties of DIF testing, in part because many latent variable methods require large samples to obtain stable parameter estimates. Much less research has evaluated these methods in small sample sizes despite the fact that many social and behavioral scientists frequently encounter small samples in practice. In this article, we examine the extent to which model complexity—the number of model parameters estimated simultaneously—affects the recovery of DIF in small samples. We compare three models that vary in complexity: logistic regression with sum scores, the 1-parameter logistic IRT model, and the 2-parameter logistic IRT model. We expected that logistic regression with sum scores and the 1-parameter logistic IRT model would more accurately estimate DIF because these models yielded more stable estimates despite being misspecified. Indeed, a simulation study and empirical example of adolescent substance use show that, even when data are generated from / assumed to be a 2-parameter logistic IRT, using parsimonious models in small samples leads to more powerful tests of DIF while adequately controlling for Type I error. We also provide evidence for minimum sample sizes needed to detect DIF, and we evaluate whether applying corrections for multiple testing is advisable. Finally, we provide recommendations for applied researchers who conduct DIF analyses in small samples.     

额叶与非额叶脑肿瘤患者分心记忆和符号数字作业的比较研究

本文以95例额叶、颞叶和顶枕叶脑肿瘤患者为被试,探讨了脑肿瘤部位同分心记忆和符号数字的关系。结果表明,额叶患者的故事意义分的分心消耗值显著高于正常人,其词的分心回忆和分心消耗值显著差于颞叶组,表明额叶在分心作业中较颞叶参与较多。右顶叶也有涉及分心注意较多的趋势,提示大脑前部可能与分心注意关系较密切。“符号数字”作业中,则“写”的作业有颞叶组好于额叶组,“说”的作业颞叶组好于顶枕组的趋势。