多阶段增长模型的方法比较

多阶段增长模型（Piecewise Growth Modeling,PGM）可以解决发展趋势中具有转折点的情形,并且相对其他复杂的曲线增长模型,解释更简单.已有的统计方法主要通过多层线性模型和潜变量增长模型对多阶段模型进行估计.通过模拟研究,用HLM6.0和Mplus6.0对上述两种模型分别进行估计,结果发现在参数估计的精度上,两种估计方法没有差异,只是在犯一类错误的概率上后者略小.进一步通过对错误模型的探讨发现,在样本量小（n=50）,斜率变化小（△b=0.2）时,用线性模型拟合数据而非PGM所犯错误概率较小,整体拟合更佳.但随着样本的增加和斜率变化的增加,错误模型的犯错概率明显增大.故在实际应用中,为了能更好拟合数据,研究者应根据数据本身的情况选择恰当的模型.     

刺激同一性对错误后反应的影响

当错误发生后,人们往往会放慢错误后反应的速度,以避免错误的再次发生,许多研究者认为,这是自上而下的认知控制对错误后反应的影响.为了探讨刺激属性是否也在错误后的反应中起作用,本研究从刺激同一性角度出发,探讨错误反应刺激与错误后刺激的同一性以及反应-刺激间隔时间(RSI)对错误后反应的影响.结果发现,当错误后的刺激与错误反应的刺激一致时,可减小错误后反应时延长的程度,同时,RSI越大,PES越小.本研究得出结论,刺激同一性和RSI作为自下而上的刺激驱动在PES的产生过程中发挥了作用.     

MEGA♪: An Ecological Risk Assessment Tool of Risk and Protective Factors for Assessing Sexually Abusive Children and Adolescents

MEGA^? is a comprehensive, ecologically framed, structured risk assessment tool for assessing sexually abusive behavior, coarse sexual improprieties, or both in all youth under 19 years, including male and female adjudicated and nonadjudicated youth, children under 12, and youth with low intellectual functioning. MEGA^?, or Multiplex Empirically Guided Inventory of Ecological Aggregates for Assessing Sexually Abusive Adolescents and Children (Ages 19 and Under; Miccio-Fonseca, 2006b Miccio-Fonseca, L. C. 2006b. Multiplex Empirically Guided Inventory of Ecological Aggregates for Assessing Sexually Abusive Children and Adolescents (Ages 19 and Under)—MEGA^?, San Diego, CA: Author.  [Google Scholar]) is composed of 7 aggregates and 4 distinct risk scales: (a) Risk Scale, (b) Protective Risk Scale, (c) Estrangement Risk Scale, and (d) Persistent Sexual Deviancy Scale. Discussed are the internal consistency findings on a sample of 1,184 (979 males and 205 females). MEGA^?'s Risk and Protective Risk Scales are discussed in depth.     

Generation of Bimanual Trajectories of Disparate Eccentricity: Levels of Interference and Spontaneous Changes Over Practice

The authors examined intermanual interactions of 2 hands that were required to concurrently follow trajectories that differed in eccentricity. Ten healthy participants attempted to learn to trace 2 figures, a circle and an ellipse, with bilaterally isochronous (1:1) timing demands. Initial unimanual trials were followed by bilateral practice comprising 750 movement cycles. Two objectives were addressed: The authors' primary aim was to determine if kinematic interlimb interference is evident independent of spatial and temporal interference and to observe the potential practice-related changes in the nature of that interference. That test was afforded by participants' natural tendency to draw a circle with a relatively constant tangential velocity and an ellipse with a systematically varying velocity. A second aim was to observe the nature of spontaneous changes in the performance of each individual effector, and in the relationship between effectors, across practice. Those objectives were specifically addressed in a context in which augmented feedback was not available to direct the learners' attention to a particular feature of performance. The results suggested that interlimb assimilation of spatial features is the primary source of interference for that task and that apparent effects at the kinematic level are the secondary, indirect product of spatial coupling. Those results were found across blocks of practice. With respect to nondirected performance changes, substantially less improvement was evident in the performance of each individual effector than in the reduction of interlimb interference. Specifically, no practice-related changes in temporal variability or velocity bias, and minimal changes in trajectory smoothness, were evident in individual limbs. Conversely, significant reductions were observed in the variability of relative phase between limbs and in the magnitude of interlimb phase lag.     

Time-specific Errors in Growth Curve Modeling: Type-1 Error Inflation and a Possible Solution with Mixed-Effects Models

Growth curve modeling (GCM) has been one of the most popular statistical methods to examine participants’ growth trajectories using longitudinal data. In spite of the popularity of GCM, little attention has been paid to the possible influence of time-specific errors, which influence all participants at each timepoint. In this article, we demonstrate that the failure to take into account such time-specific errors in GCM produces considerable inflation of type-1 error rates in statistical tests of fixed effects (e.g., coefficients for the linear and quadratic terms). We propose a GCM that appropriately incorporates time-specific errors using mixed-effects models to address the problem. We also provide an applied example to illustrate that GCM with and without time-specific errors would lead to different substantive conclusions about the true growth trajectories. Comparisons with other models in longitudinal data analysis and potential issues of model misspecification are discussed.     

Within-word serial order control: Adjacent mora exchange and serial position effects in repeated single-word production

An essential function of language processing is serial order control. Computational models of serial ordering and empirical data suggest that plan representations for ordered output of sound are governed by principles related to similarity. Among these principles, the temporal distance and edge principles at a within-word level have not been empirically demonstrated separately from other principles. Specifically, the temporal distance principle assumes that phonemes that are in the same word and thus temporally close are represented similarly. This principle would manifest as phoneme movement errors within the same word. However, such errors are rarely observed in English, likely reflecting stronger effects of syllabic constraints (i.e., phonemes in different positions within the syllable are distinctly represented). The edge principle assumes that the edges of a sequence are represented distinctly from other elements/positions. This principle has been repeatedly observed as a serial position effect in the context of phonological short-term memory. However, it has not been demonstrated in single-word production. This study provides direct evidence for the two abovementioned principles by using a speech-error induction technique to show the exchange of adjacent morae and serial position effects in Japanese four-mora words. Participants repeatedly produced a target word or nonword, immediately after hearing an aurally presented distractor word. The phonologically similar distractor words, which were created by exchanging adjacent morae in the target, induced adjacent-mora-exchange errors, demonstrating the within-word temporal distance principle. There was also a serial position effect in error rates, such that errors were mostly induced at the middle positions within a word. The results provide empirical evidence for the temporal distance and edge principles in within-word serial order control.     

Direction of dependence in measurement error models

Methods to determine the direction of a regression line, that is, to determine the direction of dependence in reversible linear regression models (e.g., x→y vs. y→x), have experienced rapid development within the last decade. However, previous research largely rested on the assumption that the true predictor is measured without measurement error. The present paper extends the direction dependence principle to measurement error models. First, we discuss asymmetric representations of the reliability coefficient in terms of higher moments of variables and the attenuation of skewness and excess kurtosis due to measurement error. Second, we identify conditions where direction dependence decisions are biased due to measurement error and suggest method of moments (MOM) estimation as a remedy. Third, we address data situations in which the true outcome exhibits both regression and measurement error, and propose a sensitivity analysis approach to determining the robustness of direction dependence decisions against unreliably measured outcomes. Monte Carlo simulations were performed to assess the performance of MOM-based direction dependence measures and their robustness to violated measurement error assumptions (i.e., non-independence and non-normality). An empirical example from subjective well-being research is presented. The plausibility of model assumptions and links to modern causal inference methods for observational data are discussed.     

Differential effects of main error correction versus secondary error correction on motor pattern of running

The aim of this study was to gain a better understanding of how the run pattern varies as a consequence to main error correction versus secondary error correction. Twenty-two university students were randomly assigned to one of two training-conditions: ‘main error’ (ME) and ‘secondary error’ (SE) correction. The rear-foot strike at touchdown was hypothesized as the ‘main error’, whereas an incorrect shoulder position (i.e., behind the base of support) as the ‘secondary error’. In order to evaluate any changes in run pattern at the foot touchdown instant, the ankle, knee and hip joint angles, the height of toe and heel (with respect to the ground), and the horizontal distance from the heel to the projected center of mass on the ground were measured. After the training-intervention, the ME group showed a significant improvement in the run pattern at the foot touchdown instant in all kinematic parameters, whereas no significant changes were found in the SE group. The results support the hypothesis that the main error can have a greater influence on the movement patterns than a secondary error. Furthermore, the findings highlight that a correct diagnosis and the correction of the ‘main error’ are fundamental for greater run pattern improvement.