On the asymptotic standard error of a class of robust estimators of ability in dichotomous item response models

In item response theory, the classical estimators of ability are highly sensitive to response disturbances and can return strongly biased estimates of the true underlying ability level. Robust methods were introduced to lessen the impact of such aberrant responses on the estimation process. The computation of asymptotic (i.e., large‐sample) standard errors (ASE) for these robust estimators, however, has not yet been fully considered. This paper focuses on a broad class of robust ability estimators, defined by an appropriate selection of the weight function and the residual measure, for which the ASE is derived from the theory of estimating equations. The maximum likelihood (ML) and the robust estimators, together with their estimated ASEs, are then compared in a simulation study by generating random guessing disturbances. It is concluded that both the estimators and their ASE perform similarly in the absence of random guessing, while the robust estimator and its estimated ASE are less biased and outperform their ML counterparts in the presence of random guessing with large impact on the item response process.     

A general linear model for estimating effect size in the presence of publication bias

When the process of publication favors studies with smallp-values, and hence large effect estimates, combined estimates from many studies may be biased. This paper describes a model for estimation of effect size when there is selection based on one-tailedp-values. The model employs the method of maximum likelihood in the context of a mixed (fixed and random) effects general linear model for effect sizes. It offers a test for the presence of publication bias, and corrected estimates of the parameters of the linear model for effect magnitude. The model is illustrated using a well-known data set on the benefits of psychotherapy.Authors' note: The contributions of the authors are considered equal, and the order of authorship was chosen to be reverse-alphabetical.     

Mueller-Lyer illusion and size estimation performance in schizophrenics compared to normal controls

A size estimation (SE) paradigm and the Mueller-Lyer (ML) illusion were used to examine perceptual disturbances in schizophrenics. 35 reliably diagnosed (DSM III-R) schizophrenics were compared to 20 subjects with no history of psychiatric illness. Perceptual distortions found in previous studies of schizophrenics were only to a certain extent confirmed in the present results. More overestimators were found among the schizophrenics than among the normals on the SE task. The schizophrenics, first of all the chronic patients, also proved to be more prone to the Mueller-Lyer illusion. A reason why the very clear differences between schizophrenics and normals found in previous examinations were not confirmed in the present study, might be that a reliable diagnostic instrument was for the first time used in this kind of study.     

An effect size measure and Bayesian analysis of single-case designs

This article describes a linear modeling approach for the analysis of single-case designs (SCDs). Effect size measures in SCDs have been defined and studied for the situation where there is a level change without a time trend. However, when there are level and trend changes, effect size measures are either defined in terms of changes in R² or defined separately for changes in slopes and intercept coefficients. We propose an alternate effect size measure that takes into account changes in slopes and intercepts in the presence of serial dependence and provides an integrated procedure for the analysis of SCDs through estimation and inference based directly on the effect size measure. A Bayesian procedure is described to analyze the data and draw inferences in SCDs. A multilevel model that is appropriate when several subjects are available is integrated into the Bayesian procedure to provide a standardized effect size measure comparable to effect size measures in a between-subjects design. The applicability of the Bayesian approach for the analysis of SCDs is demonstrated through an example.     

My face through the looking-glass: the effect of mirror reversal on reflection size estimation

People tend to grossly overestimate the size of their mirror-reflected face. Although this overestimation bias is robust, not much is known about its relationships to self-face perception. In two experiments, we investigated the overestimation bias as a function of the presentation of the own face (left–right reversed – as in a mirror – or nonreversed – as in a photograph), the identity of the seen face, and prior exposure to a real mirror. For this we developed a computerized task requiring size estimations of displayed faces. We replicated the observation that people overestimate the size of their mirror-reflected face and showed that the overestimation can be reduced following a brief mirror exposure. We also found that left–right reversal modulates the overestimation bias, depending on the perceived face’s identity. These data underline the enhanced familiarity of left–right reversed self-faces and the importance of size perception for understanding mirror reflection processing.     

元分析的特点、方法及其应用的现状分析

元分析是心理、教育及其他科学领域内新近出现的一种重要研究方法,它主要是借助统计方法,对针对同一问题的大量研究结果进行综合分析与评价,从而概括出其研究结果所反映的共同效应,即普遍性的结论。但这种方法在目前国内心理与教育研究中仍不多见。本文首先将通过与其他整合研究结果的分析方法的比较,归纳出元分析的主要特点及其局限性,其次本文着重介绍目前应用较为广泛的三种重要的元分析方法,并对三种方法作出比较分析;最后本文还将对元分析技术在国内心理学研究中的应用现状作分析与评价。     

Limited information estimation and testing of discretized multivariate normal structural models

Discretized multivariate normal structural models are often estimated using multistage estimation procedures. The asymptotic properties of parameter estimates, standard errors, and tests of structural restrictions on thresholds and polychoric correlations are well known. It was not clear how to assess the overall discrepancy between the contingency table and the model for these estimators. It is shown that the overall discrepancy can be decomposed into a distributional discrepancy and a structural discrepancy. A test of the overall model specification is proposed, as well as a test of the distributional specification (i.e., discretized multivariate normality). Also, the small sample performance of overall, distributional, and structural tests, as well as of parameter estimates and standard errors is investigated under conditions of correct model specification and also under mild structural and/or distributional misspecification. It is found that relatively small samples are needed for parameter estimates, standard errors, and structural tests. Larger samples are needed for the distributional and overall tests. Furthermore, parameter estimates, standard errors, and structural tests are surprisingly robust to distributional misspecification. This research was supported by the Department of Universities, Research and Information Society (DURSI) of the Catalan Government, and by grants BSO2000-0661 and BSO2003-08507 of the Spanish Ministry of Science and Technology.     

Limited information estimation and testing of Thurstonian models for paired comparison data under multiple judgment sampling

We relate Thurstonian models for paired comparisons data to Thurstonian models for ranking data, which assign zero probabilities to all intransitive patterns. We also propose an intermediate model for paired comparisons data that assigns nonzero probabilities to all transitive patterns and to some but not all intransitive patterns.There is a close correspondence between the multidimensional normal ogive model employed in educational testing and Thurstone's model for paired comparisons data under multiple judgment sampling with minimal identification restrictions. Alike the normal ogive model, Thurstonian models have two formulations, a factor analytic and an IRT formulation. We use the factor analytic formulation to estimate this model from the first and second order marginals of the contingency table using estimators proposed by Muthén. We also propose a statistic to assess the fit of these models to the first and second order marginals of the contingency table. This is important, as a model may reproduce well the estimated thresholds and tetrachoric correlations, yet fail to reproduce the marginals of the contingency table if the assumption of multivariate normality is incorrect.A simulation study is performed to investigate the performance of three alternative limited information estimators which differ in the procedure used in their final stage: unweighted least squares (ULS), diagonally weighted least squares (DWLS), and full weighted least squares (WLS). Both the ULS and DWLS show a good performance with medium size problems and small samples, with a slight better performance of the ULS estimator.This paper is based on the author's doctoral dissertation; Ulf Böckenholt, advisor. The final stages of this research took place while the author was at the Department of Statistics and Econometrics, Universidad Carlos III de Madrid. The author is indebted to Adolfo Hernández for stimulating discussions that helped improve this paper, and to Ulf Böckenholt and the Associate Editor for a number of helpfulsuggestions to a previous draft.     

道歉在信任修复中的作用:来自元分析的证据

采用元分析方法对道歉的信任修复效果进行探讨。通过中英文献检索,共有18篇文献36个独立样本符合元分析标准(N=4731)。元分析的结果表明,道歉在信任修复中起到一定促进作用,呈中等效应量(d=0.44)。调节效应检验发现,信任违背类型的调节作用显著,相比于诚实型信任违背,道歉对能力型信任违背有较好的修复效果。此外,控制组设置对道歉的信任修复效果具有显著的调节作用,以沉默为控制组的信任修复效果优于以否认为控制组的信任修复效果。信任类型、道歉所包含的成分以及测量工具的调节作用均不显著。     

Conditional estimation of exponential random graph models from snowball sampling designs

A complete survey of a network in a large population may be prohibitively difficult and costly. So it is important to estimate models for networks using data from various network sampling designs, such as link-tracing designs. We focus here on snowball sampling designs, designs in which the members of an initial sample of network members are asked to nominate their network partners, their network partners are then traced and asked to nominate their network partners, and so on. We assume an exponential random graph model (ERGM) of a particular parametric form and outline a conditional maximum likelihood estimation procedure for obtaining estimates of ERGM parameters. This procedure is intended to complement the likelihood approach developed by  Handcock and Gile (2010) by providing a practical means of estimation when the size of the complete network is unknown and/or the complete network is very large. We report the outcome of a simulation study with a known model designed to assess the impact of initial sample size, population size, and number of sampling waves on properties of the estimates. We conclude with a discussion of the potential applications and further developments of the approach.     

The effect of uncertainty of item parameter estimation on ability estimates

The conventional method of measuring ability, which is based on items with assumed true parameter values obtained from a pretest, is compared to a Bayesian method that deals with the uncertainties of such items. Computational expressions are presented for approximating the posterior mean and variance of ability under the three-parameter logistic (3PL) model. A 1987 American College Testing Program (ACT) math test is used to demonstrate that the standard practice of using maximum likelihood or empirical Bayes techniques may seriously underestimate the uncertainty in estimated ability when the pretest sample is only moderately large.This work was partially supported under contract No. N00014-85-K-0113, NR150-535, from the Cognitive Science Program, Office of Naval Research. The authors wish to thank Mark D. Reckase for providing the ACT data used in the illustration and two referees, Asociate Editor and Editor for helpful suggestions.     

Effects of attention and external stimuli on duration estimation under aprospective paradigm

The study examined whether there are two independent cognitive factors affecting duration estimation. In two experiments, we manipulated simultaneously and independently two variables, namely, the level of attention to the lapse of time and the quantity of perceived changes, and examined their effects on duration estimation under a prospective paradigm. The duration was estimated to be longer when subjects attended to the lapse of time than when they attended to tasks during the target interval (Experiments 1 and 2). The characteristics of external stimuli irrelevant to the tasks, namely, the rate of presentation of sounds (Experiment 1) and the velocity of moving dots (Experiment 2), affected duration estimation, even though the attention level was little changed by these stimuli. These findings suggest that there are at least two independent cognitive factors that affect duration estimation.     

Implications of accuracy, sensitivity, and variability of body size estimations to disordered eating

The current study was conducted to investigate the relationships between body size estimations and disordered eating symptomatology. The method of constant stimuli was used to derive three measures of self-perceived body size in 93 women: (1) accuracy of body size estimations (body image distortion); (2) sensitivity in discriminating body size within blocks of trials (body image sensitivity); and (3) variability in making body size estimations between blocks of trials (body image variability). Participants also completed measures of disordered eating. Although body image distortion correlated with dietary restraint and eating concern, body image variability accounted for additional variance in these variables, as well as variance in binge eating. The relationships involving body image variability were found to be mediated by body dissatisfaction and internalization of the thin ideal. Together, these results are consistent with the proposition that body image variability is a significant factor in disordered eating.     

On the loss of information in conditional maximum likelihood estimation of item parameters

In item response models of the Rasch type (Fischer & Molenaar, 1995), item parameters are often estimated by the conditional maximum likelihood (CML) method. This paper addresses the loss of information in CML estimation by using the information concept of F-information (Liang, 1983). This concept makes it possible to specify the conditions for no loss of information and to define a quantification of information loss. For the dichotomous Rasch model, the derivations will be given in detail to show the use of the F-information concept for making comparisons for different estimation methods. It is shown that by using CML for item parameter estimation, some information is almost always lost. But compared to JML (joint maximum likelihood) as well as to MML (marginal maximum likelihood) the loss is very small. The reported efficiency in the use of information of CML to JML and to MML in several comparisons is always larger than 93%, and in tests with a length of 20 items or more, larger than 99%.     

On the sampling interpretation of confidence intervals and hypothesis tests in the context of conditional maximum likelihood estimation

In the context ofconditional maximum likelihood (CML) estimation, confidence intervals can be interpreted in three different ways, depending on the sampling distribution under which these confidence intervals contain the true parameter value with a certain probability. These sampling distributions are (a) the distribution of the data given theincidental parameters, (b) the marginal distribution of the data (i.e., with the incidental parameters integrated out), and (c) the conditional distribution of the data given the sufficient statistics for the incidental parameters. Results on the asymptotic distribution of CML estimates under sampling scheme (c) can be used to construct asymptotic confidence intervals using only the CML estimates. This is not possible for the results on the asymptotic distribution under sampling schemes (a) and (b). However, it is shown that theconditional asymptotic confidence intervals are also valid under the other two sampling schemes. I am indebted to Theo Eggen, Norman Verhelst and one of Psychometrika's reviewers for their helpful comments.     

《心理统计学》教学内容的新探索

本文在对当前国内外主要心理统计学教材进行比较的基础上,指出与上个世纪八十年代的心理统计学教材内容相比较,在内容上的新探索主要体现在（1）由“假设检验”的内容中发展出“统计检验力”和“效果大小”的统计指标和估计方法;（2）引进一般线性模型来统合方差分析和回归分析这两种统计方法;（3）适度增加一些“多元统计分析”的内容等三个方面.本文对前两个方面的新内容作了简要评述,并对教材内容的编排方面提出了新的思路.     

The relative law of effect: effects of shock intensity on response strength in multiple schedules

Key pecking of four birds was reinforced with food according to a two-component multiple variable-interval 1-minute variable-interval 4-minute schedule. In addition, key pecking was punished by a brief shock according to a variable-interval 30-second schedule during both components of the multiple schedule. The intensity of the shock was varied. For all birds, punishment had a stronger suppressive effect on the responding maintained by the leaner food schedule, and the ratio of responding during the two components of the multiple schedule became closer to the ratio of reinforcement as shock intensity was increased, as the relative law of effect predicts. At the higher shock intensity, there was some evidence that the ratio of responses overmatched the ratio of reinforcements.     

Examining the lag effect under incidental encoding: Contributions of semantic priming and reminding

Memory is better when repeated learning events are spaced than when they are massed (spacing effect), as well as when material is processed semantically than when it is processed graphemically (levels-of-processing effect). Examination of the relationship between levels of processing and spacing for both deeply and shallowly encoded items has shown a spacing effect for items processed deeply, but not shallowly. A semantic priming account of spacing was proposed to explain the interaction between levels of processing and spacing on memory. The current study manipulated levels of processing and the amount of spacing (lag) that occurred between repetitions of items that were incidentally encoded. Results from Experiments 1A and 1B revealed lag effects in test performance when items were deeply and shallowly encoded. Although these findings are inconsistent with a semantic priming account, they can be interpreted within a reminding account, which is explored in Experiment 2. Results from the second experiment indicate that bringing reminding under conscious control benefited items that were presented at a long lag but not at a shorter lag. Together, this study provides evidence that is difficult to accommodate with a semantic priming account of spacing and instead provides additional support for a reminding account suggesting that automatic and controlled processes may both underlie the reminding process.     

Molecular dynamics simulations of the size effect of titanium single-crystal nanopillars orientated for double prismatic slips

An inverse “smaller is stronger” trend is predicted on the basis of molecular dynamics simulations of α-titanium (Ti) single-crystal nanopillars orientated for double prismatic slips when the nanopillars are less than 7?nm wide. This trend is attributed to a significant increase in the surface energy due to the nucleation and propagation of edge dislocations on the surface of the pillars.     

Determinants of pausing under variable-ratio schedules: Reinforcer magnitude, ratio size, and schedule configuration

Pigeons pecked a key under two-component multiple variable-ratio schedules that offered 8-s or 2-s access to grain. Phase 1 assessed the effects of differences in reinforcer magnitude on postreinforcement pausing, as a function of ratio size. In Phase 2, postreinforcement pausing and the first five interresponse times in each ratio were measured as a function of differences in reinforcer magnitude under equal variable-ratio schedules consisting of different configurations of individual ratios. Rates were also calculated exclusive of postreinforcement pause times in both phases. The results from Phase 1 showed that as ratio size increased, the differences in pausing educed by unequal reinforcer magnitudes also increased. The results of Phase 2 showed that the effects of reinforcer magnitude on pausing and IRT durations were a function of schedule configuration. Under one configuration, in which the smallest ratio was a fixed-ratio 1, pauses were unaffected by magnitude but the first five interresponse times were affected. Under the other configuration, in which the smallest ratio was a fixed-ratio 7, pauses were affected by reinforcer magnitude but the first five interresponse times were not. The effect of each configuration seemed to be determined by the value of the smallest individual ratio. Rates calculated exclusive of postreinforcement pause times were, in general, directly related to reinforcer magnitude, and the relation was shown to be a function of schedule configuration.