Evaluating Factorial Invariance: An Interval Estimation Approach Using Bayesian Structural Equation Modeling

In this study, we introduce an interval estimation approach based on Bayesian structural equation modeling to evaluate factorial invariance. For each tested parameter, the size of noninvariance with an uncertainty interval (i.e. highest density interval [HDI]) is assessed via Bayesian parameter estimation. By comparing the most credible values (i.e. 95% HDI) with a region of practical equivalence (ROPE), the Bayesian approach allows researchers to (1) support the null hypothesis of practical invariance, and (2) examine the practical importance of the noninvariant parameter. Compared to the traditional likelihood ratio test, simulation results suggested that the proposed Bayesian approach could offer additional insight into evaluating factorial invariance, thus, leading to more informative conclusions. We provide an empirical example to demonstrate the procedures necessary to implement the proposed method in applied research. The importance of and influences on the choice of an appropriate ROPE are discussed.     

Right-wing adherence and objective numeracy as predictors of minority group size perceptions and size threat reactions

Racial, ethnic, religious, and sexual minority populations are growing rapidly in the West. We investigate predictors and consequences of threat responses to perceived minority group size, and perceptions of minority group size itself. Study 1 (N = 274) finds that right-wing adherence predicts greater size threat, whereas lower numerical ability predicts larger perceived group size (confirmed in Studies 2–3). Study 2 (Sample 1, N = 124; Sample 2, N = 263) finds that the relation between right-wing adherence and prejudice toward minorities exhibits an indirect effect via group size threat (but not perceived size), explaining 35–66% of this relation. Study 3 (N = 310) finds a comparable indirect effect explaining 27–40% of this relation, even after statistically controlling for indirect effects of realistic, symbolic, and terroristic threat. These findings provide novel insights into psychological processes surrounding perceived minority group size, identifying size threat as especially crucial in understanding intergroup relations.     

Should I test more babies? Solutions for transparent data peeking

Research with infants is often slow and time-consuming, so infant researchers face great pressure to use the available participants in an efficient way. One strategy that researchers sometimes use to optimize efficiency is data peeking (or “optional stopping”), that is, doing a preliminary analysis (whether a formal significance test or informal eyeballing) of collected data. Data peeking helps researchers decide whether to abandon or tweak a study, decide that a sample is complete, or decide to continue adding data points. Unfortunately, data peeking can have negative consequences such as increased rates of false positives (wrongly concluding that an effect is present when it is not). We argue that, with simple corrections, the benefits of data peeking can be harnessed to use participants more efficiently. We review two corrections that can be transparently reported: one can be applied at the beginning of a study to lay out a plan for data peeking, and a second can be applied after data collection has already started. These corrections are easy to implement in the current framework of infancy research. The use of these corrections, together with transparent reporting, can increase the replicability of infant research.     

Social discounting and delay discounting

Social discounting was measured as the amount of money a participant was willing to forgo to give a fixed amount (usually $75) to another person. In the first experiment, amount forgone was a hyperbolic function of the social distance between the giver and receiver. In the second experiment, degree of social discounting was an increasing function of reward magnitude whereas degree of delay discounting was a decreasing function of reward magnitude. In the third experiment, the shape of the function relating delayed rewards to equally valued immediate rewards for another person was predicted from individual delay and social discount functions. All in all, the studies show that the social discount function, like delay and probability discount functions, is hyperbolic in form. Copyright © 2007 John Wiley & Sons, Ltd.     

小学儿童算术估算能力的发展

本研究深入考察了我国现阶段小学儿童算术估算能力的发展状况。通过运用自编材料对1027名儿童的团体与个别测试,发现其估算能力的发展具有如下特点：（1）明显受到题目类型的影响,但在不同年龄阶段影响又不尽相同。（2）三年级可能是整数和小数估算能力发展的一个关键期,五年级是发展分数估算能力的较好时期。（3）不同估算策略的发展进程差别相当大,不同时期都有发展的侧重点。（4）小学儿童在估算时易发生多种错误,而且不同年级均有一些典型错误。另外研究还对儿童估算能力、策略与错误类型的发展进行了深入讨论。     

Nonparametric Estimation of Standard Errors in Covariance Analysis Using the Infinitesimal Jackknife

The infinitesimal jackknife provides a simple general method for estimating standard errors in covariance structure analysis. Beyond its simplicity and generality what makes the infinitesimal jackknife method attractive is that essentially no assumptions are required to produce consistent standard error estimates, not even the requirement that the population sampled has the covariance structure assumed. Commonly used covariance structure analysis software uses parametric methods for estimating parameters and standard errors. When the population sampled has the covariance structure assumed, but fails to have the distributional form assumed, the parameter estimates usually remain consistent, but the standard error estimates do not. This has motivated the introduction of a variety of nonparametric standard error estimates that are consistent when the population sampled fails to have the distributional form assumed. The only distributional assumption these require is that the covariance structure be correctly specified. As noted, even this assumption is not required for the infinitesimal jackknife. The relation between the infinitesimal jackknife and other nonparametric standard error estimators is discussed. An advantage of the infinitesimal jackknife over the jackknife and the bootstrap is that it requires only one analysis to produce standard error estimates rather than one for every jackknife or bootstrap sample.     

Regularized Partial and/or Constrained Redundancy Analysis

Methods of incorporating a ridge type of regularization into partial redundancy analysis (PRA), constrained redundancy analysis (CRA), and partial and constrained redundancy analysis (PCRA) were discussed. The usefulness of ridge estimation in reducing mean square error (MSE) has been recognized in multiple regression analysis for some time, especially when predictor variables are nearly collinear, and the ordinary least squares estimator is poorly determined. The ridge estimation method was extended to PRA, CRA, and PCRA, where the reduced rank ridge estimates of regression coefficients were obtained by minimizing the ridge least squares criterion. It was shown that in all cases they could be obtained in closed form for a fixed value of ridge parameter. An optimal value of the ridge parameter is found by G-fold cross validation. Illustrative examples were given to demonstrate the usefulness of the method in practical data analysis situations. We thank Jim Ramsay for his insightful comments on an earlier draft of this paper. The work reported in this paper is supported by Grants 10630 from the Natural Sciences and Engineering Research Council of Canada to the first author.     

不同亚型ADHD儿童的视通道时距估计能力

本研究选取ADHD混合型儿童11名,ADHD注意缺损型儿童13名以及正常儿童15名,通过"平均估计长度"、"平均估计误差百分比"、"估计变异值"三个指标,考察不同亚型ADHD儿童在时距复制和言语估计上的稳定性和精确性。研究发现,在视觉刺激条件下,ADHD儿童的时距估计缺损并不受时距长度的影响;ADHD混合型儿童在多项任务中所表现的稳定性和精确性都差,而ADHD缺损型儿童只是稳定性差,说明ADHD混合型是ADHD中更严重的亚类型;ADHD儿童在时距估计任务中稳定性差,反映了其状态调节能力的落后。     

数学焦虑、问题形式对乘法估算的影响

采用由研究者所修订的数学焦虑量表和自行设计的估算问题,通过对大学生被试进行团体测验,考察了在纯数字运算和应用题两种情境中数学焦虑对估算加工的影响以及估算中的问题大小效应。结果显示：（1）数学焦虑情绪在纯数字与应用题两种情境下都对估算有显著影响;（2）情境对估算准确率影响显著,纯数字情境下的估算准确率显著高于应用题情境;（3）在应用题情境估算中发现明显的问题大小效应,在纯数字情境估算中却未发现该效应。     

变通的题组项目功能差异检验方法在篇章阅读测验中的应用

篇章形式的阅读测验在语文学科考试与语言能力测试中占有越来越重要的地位。篇章阅读测验是一种典型的题组测验, 因此需要采用能够处理题组效应的统计方法进行分析。在进行项目功能差异(DIF)检验时, 也需要采用与之匹配的DIF检验方法。目前能够处理题组效应的DIF检验方法主要包括变通的题组DIF检验方法和基于题组反应模型的DIF检验方法, 基于题组反应模型的DIF检验方法由于实现过程繁琐, 目前只停留在理论探讨阶段。本研究将变通的题组DIF检验方法及其效应值指标引入篇章阅读测验的DIF检验中, 能够解决篇章阅读测验中DIF检验与测量的问题, 效应值指标能够为如何处理有DIF效应的题组项目提供重要依据。本研究首先选用非题组DIF检验方法与变通的题组DIF检验方法对一份试卷进行DIF检验, 两种方法的比较结果体现了进行题组DIF检验的必要性与优越性, 然后选用变通的题组DIF检验方法中有代表性的四种方法对某阅读成就测验进行题组DIF检验。研究结果表明, 在篇章阅读测验中, 能够处理题组效应的DIF检验方法较传统的DIF检验方法具有较大的优越性。