Validity and reliability of the Very Short form of the Physical Self-Inventory among Turkish adolescents

The study aimed to test the validity and reliability of the Very Short form of the Physical Self-Inventory (PSI-VS) among a sample of 635 Turkish adolescents. These adolescents have completed the 12 original items of the PSI-VS, plus a positively worded reformulation of the single reverse-keyed item of the physical attractiveness subscale. A series of confirmatory factor analyses was used to examine the psychometric properties of the original and modified versions of the PSI-VS. Findings revealed superior psychometric properties with the modified version than with the original set of items. The modified version was thus subsequently used to examine its factor structure invariance across sexes, age groups and sport practice involvement. Results not only report that this version was fully invariant across, but also that latent means were significantly different across sexes and sport practice involvement. In sum, the Turkish modified version of the PSI-VS presents acceptable psychometric properties and may be used to repeatedly and/or intensively assess participants’ physical self-perceptions in the context of sport and exercise interventions.     

科技创新团队创新增效运营模型研究

在科技创新团队运营阶段,运用生产效率测定指标构建团队创新增效运营模型,并提出增效的重点聚集于团队活动计划,而团队计划的重点是从假设探索向实践运用的方法研究。以某企业总部及其事业部18个科技创新团队为研究对象,在两个时间节点(项目开始后的第3个月和第9个月)对创新增效要因和创新效率之间的关系进行实地调查,研究结果显示:创新增效60%~80%的要因聚集于团队活动计划,第3个月以假设探索为中心的团队活动计划对于创新增效的影响极大,而第9个月以实践为中心的团队活动计划对于创新增效的影响极大。并验证了以上两个时间节点中团队活动计划重点的差异性。     

Comparing BSEM and EUPD Estimates for Two-Group SB-MTMM Experiments

In 2018, two different approaches have been suggested to solve the estimation problems that have been detected during the analysis of the data of the two-group split ballot multi-trait multi-method (SB-MTMM experiments performed in many countries between 2002 and 2010 in the European Social Survey). One group suggested using the Bayesian estimation. The other group suggested a new estimation procedure (EUPD) that makes use of the pooled data across the different countries. In this note, we present a comparison of the results of the two approaches on the same generated data, which are comparable with the data that created problems in the ESS.     

The Impact of Varying the Number of Measurement Invariance Constraints on the Assessment of Between-Group Differences of Latent Means

The objective was to offer guidelines for applied researchers on how to weigh the consequences of errors made in evaluating measurement invariance (MI) on the assessment of factor mean differences. We conducted a simulation study to supplement the MI literature by focusing on choosing among analysis models with different number of between-group constraints imposed on loadings and intercepts of indicators. Data were generated with varying proportions, patterns, and magnitudes of differences in loadings and intercepts as well as factor mean differences and sample size. Based on the findings, we concluded that researchers who conduct MI analyses should recognize that relaxing as well as imposing constraints can affect Type I error rate, power, and bias of estimates in factor mean differences. In addition, fit indexes can be misleading in making decisions about constraints of loadings and intercepts. We offer suggestions for making MI decisions under uncertainty when assessing factor mean differences.     

中国省域高技术产业创新效率的收敛性及其影响因素研究——基于空间经济学视角

针对中国高技术产业创新效率的现实差距与创新驱动发展的经济发展路径转变问题,利用随机前沿分析方法,从创新价值链的产出视角出发构建C-D生产效率函数,对中国各省域高技术产业创新效率进行测度,然后构建空间计量模型研究中国省域高技术产业创新效率的收敛性。实证结果表明:中国省域高技术产业创新效率在整体上出现逐渐上升的态势,但表现出明显的空间异质性和显著的空间自相关性,呈现显著的集群趋势;考虑空间效应的中国省域高技术产业创新效率不仅存在着绝对收敛而且存在条件收敛,且固定资产投资对省域高技术产业创新效率产生了明显的杠杆效应,但市场竞争和政府支持对省域创新效率的影响表现为不明显。     

绿色技术创新审计指标测度方法研究

可持续发展是面向二十一世纪的全球发展战略，而绿色技术创新是实现可持续发展的根本途径。从创新投入、创新过程、创新绩效与环境现效四个方面提出了绿色技术创新审计的指标体系，并对这些审计指标进行了分析和研究，从而试图为绿色技术创新管理提供一个定量化管理的工具奠定基础。     

It Matters: Reference Indicator Selection in Measurement Invariance Tests

Conventional approaches for selecting a reference indicator (RI) could lead to misleading results in testing for measurement invariance (MI). Several newer quantitative methods have been available for more rigorous RI selection. However, it is still unknown how well these methods perform in terms of correctly identifying a truly invariant item to be an RI. Thus, Study 1 was designed to address this issue in various conditions using simulated data. As a follow-up, Study 2 further investigated the advantages/disadvantages of using RI-based approaches for MI testing in comparison with non-RI-based approaches. Altogether, the two studies provided a solid examination on how RI matters in MI tests. In addition, a large sample of real-world data was used to empirically compare the uses of the RI selection methods as well as the RI-based and non-RI-based approaches for MI testing. In the end, we offered a discussion on all these methods, followed by suggestions and recommendations for applied researchers.     

Use of hierarchical linear modeling and curriculum-based measurement for assessing academic growth and instructional factors for students with learning difficulties

The main purpose of this paper is to demonstrate how to apply the Hierarchical Linear Modeling (HLM) technique to multi-wave Curriculum-Based Measurement (CBM) measures in modeling academic growth and assessing its relations to student- and instruction-related variables. HLM has advantages over other statistical methods (e.g., repeated measures ANOVA, Structural Equation Modeling) in modeling academic growth. The advantages include allowing more flexible research designs in collecting multiple data points and estimating growth rates and their relations to correlates in more reliable, accurate ways. CBM, as a multi-wave progressmonitoring system, also has distinctive psychometric features that facilitate longitudinal research on academic skill development. These features include provision of multiple data points within short time periods, good validity and reliability, and sensitivity for detecting small degrees of change. Finally, research questions related to assessing the academic growth of students with learning difficulties and using assessment results to improve educational practices for them are discussed     

Cross-Level Invariance in Multilevel Factor Models

When modeling latent variables at multiple levels, it is important to consider the meaning of the latent variables at the different levels. If a higher-level common factor represents the aggregated version of a lower-level factor, the associated factor loadings will be equal across levels. However, many researchers do not consider cross-level invariance constraints in their research. Not applying these constraints when in fact they are appropriate leads to overparameterized models, and associated convergence and estimation problems. This simulation study used a two-level mediation model on common factors to show that when factor loadings are equal in the population, not applying cross-level invariance constraints leads to more estimation problems and smaller true positive rates. Some directions for future research on cross-level invariance in MLSEM are discussed.     

Testing measurement invariance of PISA 2015 mathematics,science, and ICT scales using the alignment method

This study investigates measurement invariance of the mathematics, science, and ICT scales across the 47 countries that participated in the PISA 2015 ICT Familiarity Questionnaire. Knowing whether the same constructs and measurements can be reliably compared across countries constitutes an important goal. The Alignment method is employed to test the measurement invariance of the three scales. The results show that mathematics and science scores are highly invariant and can be used to compare countries, whereas the ICT scale is mostly non-invariant and cannot be used to reliably compare ICT means across all participating countries. Implications and limitations are discussed.