Clarifying Heterogeneity of Daytime and Nighttime Symptoms of Posttraumatic Stress in Combat Veterans With Insomnia

Daytime and nighttime symptoms of posttraumatic stress disorder (PTSD) are common among combat veterans and military service members. However, there is a great deal of heterogeneity in how symptoms are expressed. Clarifying the heterogeneity of daytime and nighttime PTSD symptoms through exploratory clustering may generate hypotheses regarding ways to optimally match evidence-based treatments to PTSD symptom profiles. We used mixture modeling to reveal clusters based on 6 daytime and nighttime symptoms of 154 combat veterans with insomnia and varying levels of PTSD symptoms. Three clusters with increasing symptom severity were identified (n1 = 50, n2 = 70, n3 = 34). These results suggest that, among veterans with insomnia, PTSD symptoms tend to exist on a continuum of severity, rather than as a categorical PTSD diagnosis. Hypotheses regarding possible targeted treatment strategies for veterans within each identified cluster, as well as ways to generalize these methods to other groups within the military, are discussed.     

Enhancing individual and collaborative eyewitness memory with category clustering recall

Most crimes have multiple eyewitnesses. The police typically interview co-witnesses separately. In time-sensitive investigations, this could slow down evidence accumulation. Having co-witnesses collaboratively recall a crime could potentially expedite evidence accumulation. However, past research shows that collaborative group members often have conflicting retrieval strategies that disrupt each other, degrading overall recall. This cost could potentially be overcome by aligning group members’ retrieval strategies with category clustering recall (CCR), which is a retrieval strategy where information is recalled from a series of forensically relevant categories (e.g., recalling the protagonists’ appearance, then actions). This study examined the costs and benefits of collaborative eyewitness memory by having collaborative pairs of strangers, nominal pairs (i.e., two individuals whose recall is pooled) and lone individuals watch a crime and recall it using free recall or CCR. The collaborative pairs recalled the crime faster than the nominal pairs. They also recalled more correct information than individuals but less than nominal pairs, irrespective of the retrieval method. There is therefore a speed-recall completeness trade-off when collaborative groups recall crimes. Importantly, all participants recalled more correct information when using CCR. This provides initial evidence suggesting that CCR is superior to free recall. Further research examining CCR’s benefits is recommended.     

Subjective organization in the episodic memory of individuals with Parkinson’s disease associated with mild cognitive impairment

Word clustering (i.e., the ability to reproduce the same word pairs in consecutive recall trials of an unrelated word list) has been extensively investigated as a proxy of subjective organization (SO) of memorandum. In healthy subjects and in groups of brain-damaged patients, the rate of SO generally predicts accuracy of word list recall. This study aimed at evaluating SO in the performance of patients with Parkinson’s disease (PD) on a word list recall task in order to investigate the basic mechanisms of episodic memory impairment that are frequently observed in these patients. For this purpose, 56 PD patients, who were stratified according to the presence and quality of mild cognitive impairment (MCI), and a group of healthy controls (HCs) were administered a word list task and an extensive battery of neuropsychological tests. Results showed that recall accuracy on the word list task progressively decreased passing from HC to PD patients without cognitive impairment, to patients with single-domain dysexecutive MCI and to patients with multiple-domain dysexecutive and amnesic MCI. Conversely, only the latter PD group showed a lower SO score than that achieved by the other groups. In the overall PD group, correlational and regression analyses demonstrated that SO scores and a composite score of executive functions were not reciprocally related, but both provided an independent and significant contribution to the prediction of word list recall accuracy. These data are discussed in terms of the contribution of executive functions and hippocampal storage processes to the onset of memory impairment in PD.     

谱聚类算法在不同属性层级结构诊断评估中的应用

聚类分析已成功用于认知诊断评估(CDA)中,使用广泛的聚类分析方法为K-means算法,有研究已证明K-means在CDA中具有较好的聚类效果。而谱聚类算法通常比K-means分类效果更佳,本研究将谱聚类算法引进CDA,探讨了属性层级结构、属性个数、样本量和失误率对该方法的影响。研究发现：（1）谱聚类算法要比K-means提供更好的聚类结果,尤其在实验条件较苛刻时,谱聚类算法更加稳健;（2）线型结构聚类效果最好,收敛型和发散型相近,独立型结构表现较差;（3）属性个数和失误率增加后,聚类效果会下降;（4）样本量增加后,聚类效果有所提升,但K-means方法有时会有反向结果出现。     

问题发现过程认知阶段划分的探索性研究

采用建构认知模型法探索问题发现过程认知阶段的存在性及顺序性问题。基于已有研究,提出问题发现过程可划分为信息搜寻、现状表征、寻求目标、建立联系、提出问题、评价和修正问题等六个阶段的基本假设。用出声思维和秩次聚类分析的方法对高低能力组共40名大学生问题发现过程的阶段性进行考察,结果显示：六个阶段中有两对阶段出现位置非常接近,可将其进行整合,构成现状搜寻与表征、目标探索、提出问题、评价和修正问题等四个阶段。在不同问题领域与不同能力被试群体中,各认知阶段的顺序性没有差异。     

Constrained k‐means on cluster proportion and distances among clusters for longitudinal data analysis

Clustering individuals by measures of similarity or dissimilarity at trajectories of changes in longitudinal data enables determination of typical patterns of development and growth. The present research proposes a new constrained k‐means method with lower bound constraints on cluster proportions and distances among clusters at focused variables and time points to fulfill various needs in clustering longitudinal data. The method assumes a large number of clusters at the onset and iteratively deletes and combines clusters according to these constraints. An additional property of the proposed constrained k‐means includes direct estimation of the unknown number of clusters. Simulation results clearly show the usefulness of the method for extracting clusters in plausible, real‐life analysis including non‐normality within clusters, and the proposed algorithm works well and convergence of the estimates is satisfactory. An actual example using Japanese longitudinal data regarding sleep habits and mental health is presented to verify the utility of the proposed constrained k‐means.     

Serial and subjective clustering on a verbal learning test (VLT) in children aged 5–15: The nature of subjective clustering

This study investigated which strategies children aged 5–15 years (N?=?408) employ while performing a multitrial free recall test of semantically unrelated words. Serial clustering (i.e., a relatively passive strategy) is an index of the sequential consistency of recall order. Subjective clustering (i.e., a more active strategy) is based on similar word groupings in successive trials. Previously, Meijs et al. (2009 Meijs, C. J. C., Hurks, P. P. M., Kalff, A. C., Slaats-Willemse, D. I. E., Rozendaal, N. and Jolles, J. 2009. Differential development of learning strategies on a Pictorial Verbal Learning Test (PVLT) in primary school children. Child Neuropsychology, 15: 247–261. [Taylor &; Francis Online], [Web of Science ®] , [Google Scholar]) found that the level of (serial and subjective) clustering increases with age. At all ages, the level of serial clustering correlates positively with the ability to recall information on VLT trials. However, subjective clustering is more predictive of VLT performance than serial clustering after ≥ 3 trials, but only in children aged 8+. Knowledge on how children organize words (based on, for example, sound or meaning) and how this relates to developmental stage is still lacking. This study revealed that the level of subjective clustering is primarily determined by the position of words in a VLT list. More specifically, primacy (i.e., recall of words 1–3 of the VLT list — whether recalled in the same order or reversed) and recency (i.e., recall of words 14–15) effects primarily determine level subjective organization over successive trials. Thus, older children still organize words based on the serial position of the VLT list and are much less likely to organize them based on any other feature of the words, for example, sound or meaning. This indicates that the most important information to be learned needs to be presented first or last, even in older children and even with repeated presentations.     

Model based clustering of large data sets: Tracing the development of spelling ability

There are two main theories with respect to the development of spelling ability: the stage model and the model of overlapping waves. In this paper exploratory model based clustering will be used to analyze the responses of more than 3500 pupils to subsets of 245 items. To evaluate the two theories, the resulting clusters will be ordered along a developmental dimension using an external criterion. Solutions for three statistical problems will be given: (1) an algorithm that can handle large data sets and only renders non-degenerate clusters; (2) a goodness of fit test that is not affected by the fact that the number of possible response vectors by far out-weights the number of observed response vectors; and (3) a new technique,data expunction, that can be used to evaluate goodness-of-fit tests if the missing data mechanism is known. Research supported by a grant (NWO 411-21-006) of the Dutch Organization for Scientific Research.     

Indclas: A three-way hierarchical classes model

A three-way three-mode extension of De Boeck and Rosenberg's (1988) two-way two-mode hierarchical classes model is presented for the analysis of individual differences in binary object × attribute arrays. In line with the two-way hierarchical classes model, the three-way extension represents both the association relation among the three modes and the set-theoretical relations among the elements of each model. An algorithm for fitting the model is presented and evaluated in a simulation study. The model is illustrated with data on psychiatric diagnosis. Finally, the relation between the model and extant models for three-way data is discussed.The research reported in this paper was partially supported by NATO (Grant CRG.921321 to Iven Van Mechelen and Seymour Rosenberg).