概化理论预算限制下最佳样本量估计

概化理论广泛应用于各种心理测评实践中。当有预算限制时,概化理论需要考虑如何设计一个测量可靠性相对较高且可行性也相对较强的测量程序,这就要求通过某些途径估计最佳样本量。拉格朗日乘法是概化理论预算限制下最佳样本量估计较为成熟的方法。探讨了概化理论预算限制下最佳样本量估计的一些影响因素,如受总预算舍入的影响等,也提出了一些后续改善的建议,如推导出拉格朗日乘法的统一公式等     

概化理论缺失数据方差分量估计

各种心理调查、心理实验中, 数据的缺失随处可见。由于数据缺失, 给概化理论分析非平衡数据的方差分量带来一系列问题。基于概化理论框架下, 运用Matlab 7.0软件, 自编程序模拟产生随机双面交叉设计p×i×r缺失数据, 比较和探讨公式法、REML法、拆分法和MCMC法在估计各个方差分量上的性能优劣。结果表明：(1) MCMC方法估计随机双面交叉设计p×i×r缺失数据方差分量, 较其它3种方法表现出更强的优势; (2) 题目和评分者是缺失数据方差分量估计重要的影响因素。     

心理病理学网络理论、方法与挑战

对于精神障碍这一概念的理解, 传统DSM-ICD分类诊断系统和研究领域标准RDoC均基于潜变量视角, 认为精神障碍的症状由其潜在共同原因所致。这2种观点都忽略了症状间的相互作用。不同于分类和维度视角, Borsboom在2008年对精神障碍的概念化提出了的全新视角——心理病理学网络理论。此理论的核心观点是症状之间的动态因果关系构成了精神障碍。基于心理病理学网络理论的网络分析方法, 主要以结合EBIC的glasso算法估计症状间的偏相关网络, 并通过网络中节点中心性与网络连接性等指标, 来考查精神障碍症状的不同特性。近几年来, 研究者发现心理病理学网络分析方法在对症状间因果关系的推断、核心症状的识别和网络结构的可靠性与可重复性方面仍面临一些挑战。这些挑战为心理病理学网络理论与方法指明了未来可能的发展方向。     

多元概化理论在评定量表编制中的作用——以音像教材测评数据分析为例

目前多元概化理论已开始在考试、评价领域得到应用,但是很少有研究者关注其对评定量表编制的作用.本文认为多元概化理论的G研究可以估计各种效应带来的变异,能够据此(1)考察评定量表各维度和总体信度;(2)确定评定量表各维度的权重;D研究可以评估各种测量方案的信度,能够据此(3)确定评定项目的数量.这三个方面都是编制评定量表必不可少的环节,本文采用音像教材的测评数据,用实证方法展示多元概化理论对评定量表编制的指导作用.     

概化理论方差分量估计的跨分布分析

方差分量估计是进行概化理论分析的关键。采用MonteCarlo模拟技术,探讨心理与教育测量数据分布对概化理论各种方法估计方差分量的影响。数据分布包括正态、二项和多项分布,估计方法包括Traditional、Jackknife、Bootstrap和MCMC方法。结果表明:(1)Traditional方法估计正态分布和多项分布数据的方差分量相对较好,估计二项分布数据需要校正,Jackknife方法准确地估计了三种分布数据的方差分量,校正的Bootstrap方法和有先验信息的MCMC方法(MCMCinf)估计三种分布数据的方差分量结果较好;(2)心理与教育测量数据分布对四种方法估计概化理论方差分量有影响,数据分布制约着各种方差分量估计方法性能的发挥,需要加以区分地使用。     

概化理论G研究方差分量及其变异量估计影响因素

概化理论是关于行为测量可靠性的统计理论。G研究是进行概化理论分析的关键步骤,其主要目的是进行方差分量及其变异量估计。总结了影响概化理论G研究方差分量及其变异量估计的多种因素,包括估计方法、数据分布、研究设计、样本容量、模型效应和数据形态等,并指出了相关研究存在的六方面不足,如缺乏估计方法的综合比较、较少考察非正态分布数据、较少考虑不平衡或缺失数据等。     

校正的Bootstrap方法对概化理论方差分量及其变异量估计的改善

Bootstrap方法是一种有放回的再抽样方法, 可用于概化理论的方差分量及其变异量估计。用Monte Carlo技术模拟四种分布数据, 分别是正态分布、二项分布、多项分布和偏态分布数据。基于p×i设计, 探讨校正的Bootstrap方法相对于未校正的Bootstrap方法, 是否改善了概化理论估计四种模拟分布数据的方差分量及其变异量。结果表明：跨越四种分布数据, 从整体到局部, 不论是“点估计”还是“变异量”估计, 校正的Bootstrap方法都要优于未校正的Bootstrap方法, 校正的Bootstrap方法改善了概化理论方差分量及其变异量估计。     

概化理论不同评分方案缺失数据方差分量估计

包含评分者侧面的测验通常不符合任意一种概化理论设计,因此从概化理论的角度来看这类测验下的数据应属于缺失数据,而决定缺失结构的就是测验的评分方案。用R软件模拟出三种评分方案下的数据,并比较传统法、评价法和拆分法在各评分方案下的估计效果,结果表明：（1）传统法估计准确性较差;（2）评分者一致性较高时,适宜用评价法进行估计;（3）拆分法的估计结果最准确,仅在固定评分者评分方案下需注意评分者与考生数量之比,该比值小于等于0.0047 时估计结果较为准确。     

概化理论不同评分方案缺失数据方差分量估计

包含评分者侧面的测验通常不符合任意一种概化理论设计,因此从概化理论的角度来看这类测验下的数据应属于缺失数据,而决定缺失结构的就是测验的评分方案。用R软件模拟出三种评分方案下的数据,并比较传统法、评价法和拆分法在各评分方案下的估计效果,结果表明：（1）传统法估计准确性较差;（2）评分者一致性较高时,适宜用评价法进行估计;（3）拆分法的估计结果最准确,仅在固定评分者评分方案下需注意评分者与考生数量之比,该比值小于等于0.0047 时估计结果较为准确。     

高校教师教学水平评价概化理论预算限制下最佳样本量估计

使用“高校教师教学水平评价问卷”,要求566名学生对19名教师进行评价,对收集到的数据作不同的概化设计,包括t×i、（s：t）×i、（s：t）×（i：v）和（s：t）×（i：v）×o四种设计。基于概化理论,结合预算限制,统一LaGrange乘法公式,自行推导不同设计的最佳样本量公式,联合估计的方差分量,计算出不同设计的最佳样本量。结果表明：（1）LaGrange乘法统一公式表现出较强的通用性,能够适用于预算限制下各种概化设计;（2）评价场合是影响高校教师教学水平评价一个相当重要的因素;（3）（s：t）×（i：v）×o是高校教师教学水平评价概化理论预算限制下最优概化设计;（4）高校教师教学水平评价概化理论预算限制下,每位教师最佳评价学生人数为20人,每个维度最佳评价题目数为3题。     

中文版无手机恐惧量表的修订

该研究以国外学者Caglar Yildirim和Ana-Paula Correia于2015年编制的Nomophobia量表为基础,修订出了适用于国内的中文版无手机恐惧量表。研究首先使用探索性结构方程模型对量表结构进行初探; 其次使用项目反应模型进行项目分析并根据其分析结果对项目进行修改和筛选,最终形成正式版量表; 最后对正式版量表其进行信效度检验,并再次对量表题目进行项目分析。最终量表共16道题目,包括害怕无法获得信息、害怕失去便利、害怕失去联系和害怕失去网络连接4个维度; 总量表的Cronbach α系数为0.931,四维度的α系数分别为:0.789,0.816,0.887和0.896。CFA验证性结果显示量表结构较好(χ2/df=3.91,RMSEA=0.067,TLI=0.941,CFI=0.952,SRMR=0.04); 使用手机成瘾倾向量表作为校标的结果显示二者之间相关为0.626,效度良好。最终量表项目区分度在[1.734,4.806]之间,四维度区分度均值为2.1765,2.72,3.2925和3.883,项目难度参数在[-1.830,4.806]之间。综上结果显示该研究编制的无手机恐惧量表各项指标均达到了心理测量学要求,可供后续研究使用     

人事测评中的概化理论应用

概化理论是现代心理与教育测量理论之一,可应用在各种人事测评中,如表现性评价、多源评估、心理测验、结构化面试、水平测试、工作分析、评价中心等.与经典测量理论相比,概化理论应用于人事测评,表现出较强的优势,能够同时考察多种因素、确定多个维度权重等,其应用对象主要包括两大类,即企业和机构.概化理论应用于人事测评,存在应用领域、样本数据、测评效度和微观分析等问题.     

SCIENTIFIC METHOD AND REPRODUCIBILITY OF RESULTS

Statistical significance is not part of the scientific method. The three canons of reproducibility of an experiment: Data Matrix Homegeneity, Subject Generalizability, and Method Generalizability provide better guides to experimentation and theory development. As adjuncts to Scientific Method they provide a better basis for evaluation of statistical findings.     

Sample size planning with the cost constraint for testing superiority and equivalence of two independent groups

The allocation of sufficient participants into different experimental groups for various research purposes under given constraints is an important practical problem faced by researchers. We address the problem of sample size determination between two independent groups for unequal and/or unknown variances when both the power and the differential cost are taken into consideration. We apply the well‐known Welch approximate test to derive various sample size allocation ratios by minimizing the total cost or, equivalently, maximizing the statistical power. Two types of hypotheses including superiority/non‐inferiority and equivalence of two means are each considered in the process of sample size planning. A simulation study is carried out and the proposed method is validated in terms of Type I error rate and statistical power. As a result, the simulation study reveals that the proposed sample size formulas are very satisfactory under various variances and sample size allocation ratios. Finally, a flowchart, tables, and figures of several sample size allocations are presented for practical reference.     

Cinematic Creativity and Production Budgets: Does Money Make the Movie?

Although filmmaking requires substantial capital investment, it is not known whether cinematic creativity is positively correlated with the size of the film's budget. Therefore, budgetary impact was investigated in a sample of feature films released between 1997 and 2001. Although production costs were positively related to box office success (as measured by both first weekend and gross), such expenditures had no correlation with best picture awards and were negatively correlated with critical acclaim (as gauged by both film reviews and movie guide ratings). These divergent consequences could be partly interpreted in terms of how the budget and success criteria differentially correlated with what have been identified as the four creative clusters of filmmaking, namely, the dramatic, visual, technical, and musical.     

Leiter-3 generalizability in Scandinavia

The Leiter-3 is a nonverbal assessment that evaluates cognitive abilities and has been adapted for use in Scandinavia. Generalizability of United States-based normative scoring for use with the Scandinavian population was evaluated. Leiter-3 scores from a sample of Scandinavian students were compared with scores obtained from the Leiter-3 standardization sample, controlling for confounding variables, across ages, using mixed-methods analysis. A Scandinavian-population-based sample was created from Leiter-3 standardization data and norms were constructed and were used to generate standardized scores from the sample data. Results suggest that overall the Scandinavian test-takers score higher than American test-takers, but that differences between groups were minimized when controlling for factors that may influence cognitive performance. Creating Scandinavian based scores was not effective at reducing gaps in performance, suggesting that differences in performance between the different populations may be attributable to factors other than those typically controlled for when constructing standardized tests. Implications of these results and recommendations for Leiter-3 adaptation are reviewed.     

Parenting and adolescent well-being in two European countries

The main and interactive effects of parental behavioral control and parental support on adolescent adjustment were examined with students ages 15-19 in Italy (N = 391, 59.1% male) and The Netherlands (N = 373, 45.3% male). In general, parental support was associated with better adjustment and parental control was associated with worse adjustment. However, parental control as well as age and sex moderated the effects of parental support on psychological discomfort and expectations of future success. Positive self-perceptions were less well predicted. Further, there were more moderated effects in the Dutch sample than in the Italian sample. Generalizability of the contributions of parenting behavior to adolescent adjustment outside of a North American context is discussed.     

Optimal sample sizes for Welch’s test under various allocation and cost considerations

The issue of the sample size necessary to ensure adequate statistical power has been the focus of considerableattention in scientific research. Conventional presentations of sample size determination do not consider budgetary and participant allocation scheme constraints, although there is some discussion in the literature. The introduction of additional allocation and cost concerns complicates study design, although the resulting procedure permits a practical treatment of sample size planning. This article presents exact techniques for optimizing sample size determinations in the context of Welch (Biometrika, 29, 350–362, 1938) test of the difference between two means under various design and cost considerations. The allocation schemes include cases in which (1) the ratio of group sizes is given and (2) one sample size is specified. The cost implications suggest optimally assigning subjects (1) to attain maximum power performance for a fixed cost and (2) to meet adesignated power level for the least cost. The proposed methods provide useful alternatives to the conventional procedures and can be readily implemented with the developed R and SAS programs that are available as supplemental materials from brm.psychonomic-journals.org/content/supplemental.