How Do Propensity Score Methods Measure Up in the Presence of Measurement Error? A Monte Carlo Study

Considering that the absence of measurement error in research is a rare phenomenon and its effects can be dramatic, we examine the impact of measurement error on propensity score (PS) analysis used to minimize selection bias in behavioral and social observational studies. A Monte Carlo study was conducted to explore the effects of measurement error on the treatment effect and balance estimates in PS analysis across seven different PS conditioning methods. In general, the results indicate that even low levels of measurement error in the covariates lead to substantial bias in estimates of treatment effects and concomitant reduction in confidence interval coverage across all methods of conditioning on the PS.     

The impact of error frequency on errorless and errorful learning of object locations using a novel paradigm

ABSTRACT

Errorless learning (EL) is an approach in which errors are eliminated or reduced as much as possible while learning of new information or skills. In contrast, during trial-and-error???or errorful???learning (TEL) errors are not reduced and are often even promoted. There is a complex and conflicting pattern of evidence whether EL or TEL may result in better memory performance. One major confound in the extant literature is that most EL studies have not controlled for the number of errors made during TEL, resulting in a large variability in the amount of errors committed. This variability likely explains why studies on the cognitive underpinnings of EL and TEL have produced mixed findings. In this study, a novel object-location learning task was employed to examine EL and TEL in 30 healthy young adults. The number of errors was systematically manipulated, allowing us to investigate the impact of frequency of errors on learning outcome. The results showed that recall from memory was significantly better during EL. However, the number of errors made during TEL did not influence the performance in young adults. Altogether, our novel paradigm is promising for measuring EL and TEL, allowing for more accurate analyses to understand the impact of error frequency on a person’s learning ability and style.     

Statistical Significance Levels of Nonparametric Tests Biased by Heterogeneous Variances of Treatment Groups

The statistical significance levels of the Wilcoxon-Mann-Whitney test and the Kruskal-Wallis test are substantially biased by heterogeneous variances of treatment groups—even when sample sizes are equal. Under these conditions, the Type I error probabilities of the nonparametric tests, performed at the .01, .05, and .10 significance levels, increase by as much as 40%-50% in many cases and sometimes as much as 300%. The bias increases systematically as the ratio of standard deviations of treatment groups increases and remains fairly constant for various sample sizes. There is no indication that Type I error probabilities approach the significance level asymptotically as sample size increases.     

Rule Following,Error Theory and Eliminativism

Abstract

In this paper, I argue for three main claims. First, that there are two broad sorts of error theory about a particular region of thought and talk, eliminativist error theories and non-eliminativist error theories. Second, that an error theory about rule following can only be an eliminativist view of rule following, and therefore an eliminativist view of meaning and content on a par with Paul Churchland’s prima facie implausible eliminativism about the propositional attitudes. Third, that despite some superficial appearances to the contrary, non-eliminativist error theory does not provide a plausible vehicle for understanding the ‘sceptical solution’ to the sceptical paradox about rule-following developed in Saul Kripke’s Wittgenstein on Rules and Private Language.     

初中生学业错误的实然观与应然观关系研究

运用《初中生学业错误实然观问卷》和《初中生学业错误应然观问卷》调查了453名初中生的学业错误观,结果表明：（1）初中生学业错误的实然观与应然观均表现出显著的年级特征和性别差异;（2）初中生学业错误的应然观对实然观具有显著正向预测效用。     

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.     

Brain lateralization of complex movement: Neuropsychological evidence from unilateral stroke

Complex movement (CM) refers to the representation of a goal-oriented action and is classified as either transitive (use of tools) or intransitive (communication gestures). Both types of CM have three specific components: temporal, spatial, and content, which are subdivided into specific error types (SET). Since there is debate regarding the contribution of each brain hemisphere for the types of CM, our objective was to describe the brain lateralization of components and SET of transitive and intransitive CM. We studied 14 patients with a left hemisphere stroke (LH), 12 patients with a right hemisphere stroke (RH), and 16 control subjects. The Florida Apraxia Screening Test-Revised (FAST-R, Rothi et al., 1988) was used for the assessment of CM. Both clinical groups showed a worse performance than the control group on the total FAST-R and transitive movement scores (p < 0.001). Failures in Spatial and Temporal components were found in both clinical groups, but only LH patients showed significantly more Content errors (p < 0.01) than the control group. Also, only the LH group showed a higher number of errors for intransitive movements score (p = 0.017), due to lower scores in the content component, compared to the control group (p = 0.04). Transitive and intransitive CMs differ in their neurocognitive representation; transitive CM shows a bilateral distribution of its components when compared to intransitive CM, which shows a preferential left hemisphere representation. This could result from higher neurocognitive demands for movements that require use of tools, compared with more automatic communication gestures.     

Good News for Moral Error Theorists: A Master Argument Against Companions in Guilt Strategies

Moral error theories are often rejected by appeal to ‘companions in guilt’ arguments. The most popular form of companions in guilt argument takes epistemic reasons for belief as a ‘companion’ and proceeds by analogy. I show that this strategy fails. I claim that the companions in guilt theorist must understand epistemic reasons as evidential support relations if her argument is to be dialectically effective. I then present a dilemma. Either epistemic reasons are evidential support relations or they are not. If they are not, then the companions in guilt argument fails. If they are, then a reduction of epistemic reasons to evidential support relations becomes available and, consequently, epistemic reasons cease to be a viable ‘companion’ for moral reasons. I recommend this structure of argument over existing strategies within the literature and defend my claims against recent objections from companions in guilt theorists.