More on EM for ML factor analysis

We address several issues that are raised by Bentler and Tanaka's [1983] discussion of Rubin and Thayer [1982]. Our conclusions are: standard methods do not completely monitor the possible existence of multiple local maxima; summarizing inferential precision by the standard output based on second derivatives of the log likelihood at a maximum can be inappropriate, even if there exists a unique local maximum; EM and LISREL can be viewed as complementary, albeit not entirely adequate, tools for factor analysis.This work was partially supported by the Program Statistics Research Project at Educational Testing Service.     

Probabilistic multidimensional scaling: Complete and incomplete data

Simple procedures are described for obtaining maximum likelihood estimates of the location and uncertainty parameters of the Hefner model. This model is a probabilistic, multidimensional scaling model, which assigns a multivariate normal distribution to each stimulus point. It is shown that for such a model, standard nonmetric and metric algorithms are not appropriate. A procedure is also described for constructing incomplete data sets, by taking into consideration the degree of familiarity the subject has for each stimulus. Maximum likelihood estimates are developed both for complete and incomplete data sets. This research was supported by National Science Grant No. SOC76-20517. The first author would especially like to express his gratitude to the Netherlands Institute for Advanced Study for its very substantial help with this research.     

On Green's best linear composites with a specified structure,and oblique estimates of factor scores

Green solved the problem of least-squares estimation of several criteria subject to the constraint that the estimates have an arbitrary fixed covariance or correlation matrix. In the present paper an omission in Green's proof is discussed and resolved. Furthermore, it is shown that some recently published solutions for estimating oblique factor scores are special cases of Green's solution for the case of fixed covariance matrices.     

Pseudo maximum likelihood estimation and a test for misspecification in mean and covariance structure models

Using the theory of pseudo maximum likelihood estimation the asymptotic covariance matrix of maximum likelihood estimates for mean and covariance structure models is given for the case where the variables are not multivariate normal. This asymptotic covariance matrix is consistently estimated without the computation of the empirical fourth order moment matrix. Using quasi-maximum likelihood theory a Hausman misspecification test is developed. This test is sensitive to misspecification caused by errors that are correlated with the independent variables. This misspecification cannot be detected by the test statistics currently used in covariance structure analysis.For helpful comments on a previous draft of the paper we are indebted to Kenneth A. Bollen, Ulrich L. Küsters, Michael E. Sobel and the anonymous reviewers of Psychometrika. For partial research support, the first author wishes to thank the Department of Sociology at the University of Arizona, where he was a visiting professor during the fall semester 1987.     

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。     

改进的MCMC算法及其在估计IRT模型参数中的应用

本文首先简要的阐述了MCMC算法的思想及在IRT参数估计中的操作过程;其次,针对该算法存在的一些问题,提出相应的改进建议;然后,分别运用传统的和改进型的MCMC算法进行模拟数据分析和比较,结果显示新的方法表现更好;最后总结新方法的优点所在,并指出下一步的研究方向。     

短时距估计中的心理影响因素

使用单任务研究程序,预期式研究范式,以产生时距作为反应指标,通过两个实验考察短时距估计中的间断位置、间断时距和提示线索效应,探讨产生时距与等待时距的关系问题,揭示注意和间断期望对短时距估计的影响。研究结果表明, 间断实验中表现出极其显著的提示线索效应,间断位置（等待时距）效应显著,间断时距效应及间断位置与间断时距的交互效应不显著。由此得出：(1)注意是影响被试时间判断的主要因素,被试的产生时距随着等待时距的增加而延长。(2)被试对间断的期望显著地影响其时间估计行为,无间断实验条件下,间断期望有损于时间估计。     

自尊水平、事件效价与时距对过去事件时距估计的影响

在西方文化背景下提出的时间自我评价理论认为,人们为了维护当前积极自尊,主观上会远离过去失败而亲近过去成功。本研究采用线段评估法,选取311名中国大学生被试,通过两个实验考察自尊水平、事件效价与时距对过去事件时距估计的影响,以检验该理论的文化普适性。结果表明:对过去事件的时距估计,自尊水平、事件效价及其交互作用在同一时距里均不存在显著差异;时距的主效应及其与事件效价的交互作用均显著,在负效价水平上存在显著时距差异,在正效价水平上无显著时距差异。研究结果不支持基于西方文化背景下的时间自我评价理论。     

基于GRM模型的BP神经网络参数估计

目前参数估计多采用统计方法,存在耗时长、要求被试样本容量大和项目数多等缺点。本文将BP神经网络和降维法相结合,对GRM的项目参数和考生能力参数进行估计。蒙特卡洛模拟结果显示：（1）不管是人多题少还是题多人少,该网络设计下的参数估计精度都较高;（2）可以应用到多个不同等级评分的参数估计中,甚至是超过15个等级的项目参数,估计精度也较高,这是其他参数估计方法所不可比拟的;（3）运行的时长和统计估计方法相比大大缩减。     

算术策略运用能力的年龄差异：元认知监测与算术知识的作用

采用选择/无选法,以估算与精确心算为研究任务,考察了元认知监测与算术知识影响个体算术计算策略选择与执行的年龄相关差异。129名不同年龄儿童与成人被试参加实验。结果发现：（1）算术知识对儿童及成人的估算复杂策略有促进作用,并对提升他们心算策略运用的速度和减少错误有作用;（2）元认知监测显著影响儿童的估算策略选择,能够促进使用最佳策略;（3）算术知识在估算及心算策略执行的年龄差异方面起完全中介作用,元认知监测则在估算策略选择的年龄发展中起部分中介作用;（4）算术知识对元认知监测在估算及心算策略执行上的作用起完全中介作用,而对估算的策略选择则不存在中介作用,这表明元认知监测在估算策略选择上具有举足轻重的地位。