Evoked and event-related potentials in disorders of consciousness: A quantitative review

Sixty-one publications about evoked and event-related potentials (EP and ERP, respectively) in patients with severe Disorders of Consciousness (DoC) were found and analyzed from a quantitative point of view. Most studies are strongly underpowered, resulting in very broad confidence intervals (CI). Results of such studies cannot be correctly interpreted, because, for example, CI > 1 (in terms of Cohen’s d) indicate that the real effect may be very strong, very weak, or even opposite to the reported effect. Furthermore, strong negative correlations were obtained between sample size and effect size, indicating a possible publication bias. These correlations characterized not only the total data set, but also each thematically selected subset. The minimal criteria of a strong study to EP/ERP in DoC are proposed: at least 25 patients in each patient group; as reliable diagnosis as possible; the complete report of all methodological details and all details of results (including negative results); and the use of appropriate methods of data analysis. Only three of the detected 60 studies (5%) satisfy these criteria. The limitations of the current approach are also discussed.     

Cross-Sectional Analysis of Longitudinal Mediation Processes

Statistical mediation analysis can help to identify and explain the mechanisms behind psychological processes. Examining a set of variables for mediation effects is a ubiquitous process in the social sciences literature; however, despite evidence suggesting that cross-sectional data can misrepresent the mediation of longitudinal processes, cross-sectional analyses continue to be used in this manner. Alternative longitudinal mediation models, including those rooted in a structural equation modeling framework (cross-lagged panel, latent growth curve, and latent difference score models) are currently available and may provide a better representation of mediation processes for longitudinal data. The purpose of this paper is twofold: first, we provide a comparison of cross-sectional and longitudinal mediation models; second, we advocate using models to evaluate mediation effects that capture the temporal sequence of the process under study. Two separate empirical examples are presented to illustrate differences in the conclusions drawn from cross-sectional and longitudinal mediation analyses. Findings from these examples yielded substantial differences in interpretations between the cross-sectional and longitudinal mediation models considered here. Based on these observations, researchers should use caution when attempting to use cross-sectional data in place of longitudinal data for mediation analyses.     

Misspecification in Latent Change Score Models: Consequences for Parameter Estimation,Model Evaluation,and Predicting Change

Latent change score models (LCS) are conceptually powerful tools for analyzing longitudinal data (McArdle & Hamagami, 2001). However, applications of these models typically include constraints on key parameters over time. Although practically useful, strict invariance over time in these parameters is unlikely in real data. This study investigates the robustness of LCS when invariance over time is incorrectly imposed on key change-related parameters. Monte Carlo simulation methods were used to explore the impact of misspecification on parameter estimation, predicted trajectories of change, and model fit in the dual change score model, the foundational LCS. When constraints were incorrectly applied, several parameters, most notably the slope (i.e., constant change) factor mean and autoproportion coefficient, were severely and consistently biased, as were regression paths to the slope factor when external predictors of change were included. Standard fit indices indicated that the misspecified models fit well, partly because mean level trajectories over time were accurately captured. Loosening constraint improved the accuracy of parameter estimates, but estimates were more unstable, and models frequently failed to converge. Results suggest that potentially common sources of misspecification in LCS can produce distorted impressions of developmental processes, and that identifying and rectifying the situation is a challenge.     

Exploring a Source of Uneven Score Equity across the Test Score Range

Score equity assessment (SEA) refers to an examination of population invariance of equating across two or more subpopulations of test examinees. Previous SEA studies have shown that score equity may be present for examinees scoring at particular test score ranges but absent for examinees scoring at other score ranges. No studies to date have performed research for the purpose of understanding why score equity can be inconsistent across the score range of some tests. The purpose of this study is to explore a source of uneven subpopulation score equity across the score range of a test. It is hypothesized that the difficulty of anchor items displaying differential item functioning (DIF) is directly related to the score location at which issues of score inequity are observed. The simulation study supports the hypothesis that the difficulty of DIF items has a systematic impact on the uneven nature of conditional score equity.     

大学生自信与成就动机、综合测评成绩的相关研究

通过对289名大学生成就动机、自信的测试,探讨大学生自信与成就动机、综合测评成绩之间的关系。结果表明：(1)大学生成就动机与自信相关显著。其中,追求成功的动机与自信诸维度呈显著正相关,而避免失败的动机与自信诸维度之间则呈显著负相关;(2)综合测评成绩与自信的少数维度有显著相关,与学生成就动机之间相关不显著。     

The construct of psychophysiological reactivity: Statistical and psychometric issues

The purpose of this paper is to review major statistical and psychometric issues impacting the study of psychophysiological reactivity and discuss their implications for applied developmental researchers. We first cover traditional approaches such as the observed difference score (DS) and the observed residual score (RS), including a review of classic and recent research on their reliability and validity from two related bodies of work: the measurement of change and the Law of Initial Values. Second, we review several types of latent variable modeling in this context: latent difference score (LDS) models, latent residual score (LRS) models, latent state-trait (LST) models, and latent growth curve (LGC) models. Finally, we provide broad guidelines for applied researchers broken down by key stages of a psychophysiological project: study planning, data analysis, and reporting of results. Our recommendations highlight the need for (1) increased attention to the ubiquitous nature of measurement error in observed variables and the importance of employing latent variable models when possible, and (2) increased specification of theories relating to the construct of reactivity, especially in regards to the distinction between baseline arousal and change over time in broader systems of variables.     

掩蔽刺激的空间参考框架对视觉表象旋转的影响

本实验通过将具有参考框架信息的前置刺激改为掩蔽刺激,进一步探讨参考框架的变化和表象旋转的过程。结果表明：１、因掩蔽刺激而引起的主观参考框架的产生是瞬间完成的,而不是由原先直立的参考框架经过连续旋转后形成的。２、显示了倾斜字母的加工不完全是整体表象的线性旋转过程,而可能是整字一成分的混合加工过程。     

Approximate interval estimation for a certain intraclass correlation coefficient

When the raters participating in a reliability study are a random sample from a larger population of raters, inferences about the intraclass correlation coefficient must be based on the three mean squares from the analysis of variance table summarizing the results: between subjects, between raters, and error. An approximate confidence interval for the parameter is presented as a function of these three mean squares.Dr. Fleiss is also with the Biometrics Research Unit of the New York State Psychiatric Institute. This work was supported in part by grant DE 04068 from the National Institute of Dental Research.