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1.
Bootstrapping approximate fit indexes in structural equation modeling (SEM) is of great importance because most fit indexes do not have tractable analytic distributions. Model-based bootstrap, which has been proposed to obtain the distribution of the model chi-square statistic under the null hypothesis (Bollen & Stine, 1992), is not theoretically appropriate for obtaining confidence intervals (CIs) for fit indexes because it assumes the null is exactly true. On the other hand, naive bootstrap is not expected to work well for those fit indexes that are based on the chi-square statistic, such as the root mean square error of approximation (RMSEA) and the comparative fit index (CFI), because sample noncentrality is a biased estimate of the population noncentrality. In this article we argue that a recently proposed bootstrap approach due to Yuan, Hayashi, and Yanagihara (YHY; 2007) is ideal for bootstrapping fit indexes that are based on the chi-square. This method transforms the data so that the “parent” population has the population noncentrality parameter equal to the estimated noncentrality in the original sample. We conducted a simulation study to evaluate the performance of the YHY bootstrap and the naive bootstrap for 4 indexes: RMSEA, CFI, goodness-of-fit index (GFI), and standardized root mean square residual (SRMR). We found that for RMSEA and CFI, the CIs under the YHY bootstrap had relatively good coverage rates for all conditions, whereas the CIs under the naive bootstrap had very low coverage rates when the fitted model had large degrees of freedom. However, for GFI and SRMR, the CIs under both bootstrap methods had poor coverage rates in most conditions.  相似文献   

2.
ObjectiveThe Childhood Trauma Questionnaire-Short Form (CTQ-SF) is a self-report questionnaire that retrospectively provides screening for a history of childhood abuse and neglect, and which is widely used throughout the world. The current study aimed to examine the psychometric properties of the Chinese version of the CTQ-SF.MethodsParticipants included 3431 undergraduates from Hunan provinces and 234 depressive patients from psychological clinics. Confirmatory factor analysis was performed to examine how well the original five-factor model fit the data and the measurement equivalence of CTQ-SF across gender. Internal consistency was also evaluated.ResultsThe five-factor model achieved satisfactory fit (Undergraduate sample TLI = 0.925, CFI = 0.936, RMSEA = 0.034, SRMR = 0.046; depressive sample TLI = 0.912, CFI = 0.923, RMSEA = 0.044, SRMR = 0.062). Measurement invariance of the five-factor model across gender was supported fully assuming different degrees of invariance. The CTQ-SF also showed acceptable internal consistency and good stability.ConclusionThe current study provides that the Chinese version of the Childhood Trauma questionnaire-short form has good reliability and validity among Chinese undergraduates and depressive samples, which also indicates that the CTQ-SF is a good tool for child trauma assessment.  相似文献   

3.
In previous research (Hu & Bentler, 1998, 1999), 2 conclusions were drawn: standardized root mean squared residual (SRMR) was the most sensitive to misspecified factor covariances, and a group of other fit indexes were most sensitive to misspecified factor loadings. Based on these findings, a 2-index strategy-that is, SRMR coupled with another index-was proposed in model fit assessment to detect potential misspecification in both the structural and measurement model parameters. Based on our reasoning and empirical work presented in this article, we conclude that SRMR is not necessarily most sensitive to misspecified factor covariances (structural model misspecification), the group of indexes (TLI, BL89, RNI, CFI, Gamma hat, Mc, or RMSEA) are not necessarily more sensitive to misspecified factor loadings (measurement model misspecification), and the rationale for the 2-index presentation strategy appears to have questionable validity.  相似文献   

4.
The Classroom Appraisal of Resources and Demands (CARD, elementary version) was used to investigate teacher stress among a sample of elementary teachers (n = 521). The CARD measures teacher stress by examining the subjective experience of both classroom demands and resources provided by the school, and thereby attempts to capture the situationally specific nature of teacher stress. This study attempted to examine whether the CARD can provide reliable and valid information that addresses the call by experts in the field of teacher stress research for measures that consider each teacher's specific occupational circumstances. Specifically, the factor structure of the CARD was supported empirically. Further evidence was offered for the construct and concurrent validity by correlations between CARD scales scores and other measures theoretically relevant to teacher well‐being: general health, teacher efficacy, self‐critical attitudes, and burnout symptoms. © 2009 Wiley Periodicals, Inc.  相似文献   

5.
Model fit indices are being increasingly recommended and used to select the number of factors in an exploratory factor analysis. Growing evidence suggests that the recommended cutoff values for common model fit indices are not appropriate for use in an exploratory factor analysis context. A particularly prominent problem in scale evaluation is the ubiquity of correlated residuals and imperfect model specification. Our research focuses on a scale evaluation context and the performance of four standard model fit indices: root mean square error of approximate (RMSEA), standardized root mean square residual (SRMR), comparative fit index (CFI), and Tucker–Lewis index (TLI), and two equivalence test-based model fit indices: RMSEAt and CFIt. We use Monte Carlo simulation to generate and analyze data based on a substantive example using the positive and negative affective schedule (N = 1,000). We systematically vary the number and magnitude of correlated residuals as well as nonspecific misspecification, to evaluate the impact on model fit indices in fitting a two-factor exploratory factor analysis. Our results show that all fit indices, except SRMR, are overly sensitive to correlated residuals and nonspecific error, resulting in solutions that are overfactored. SRMR performed well, consistently selecting the correct number of factors; however, previous research suggests it does not perform well with categorical data. In general, we do not recommend using model fit indices to select number of factors in a scale evaluation framework.  相似文献   

6.
Two Monte Carlo studies were conducted to examine the sensitivity of goodness of fit indexes to lack of measurement invariance at 3 commonly tested levels: factor loadings, intercepts, and residual variances. Standardized root mean square residual (SRMR) appears to be more sensitive to lack of invariance in factor loadings than in intercepts or residual variances. Comparative fit index (CFI) and root mean square error of approximation (RMSEA) appear to be equally sensitive to all 3 types of lack of invariance. The most intriguing finding is that changes in fit statistics are affected by the interaction between the pattern of invariance and the proportion of invariant items: when the pattern of lack of invariance is uniform, the relation is nonmonotonic, whereas when the pattern of lack of invariance is mixed, the relation is monotonic. Unequal sample sizes affect changes across all 3 levels of invariance: Changes are bigger when sample sizes are equal rather than when they are unequal. Cutoff points for testing invariance at different levels are recommended.  相似文献   

7.
We compare the accuracy of confidence intervals (CIs) and tests of close fit based on the root mean square error of approximation (RMSEA) with those based on the standardized root mean square residual (SRMR). Investigations used normal and nonnormal data with models ranging from p = 10 to 60 observed variables. CIs and tests of close fit based on the SRMR are generally accurate across all conditions (even at p = 60 with nonnormal data). In contrast, CIs and tests of close fit based on the RMSEA are only accurate in small models. In larger models (p ≥ 30), they incorrectly suggest that models do not fit closely, particularly if sample size is less than 500.  相似文献   

8.
Parental involvement is well documented as a significant contributor to the self‐efficacy and academic achievement of students. A structural equation model of parent involvement with family socioeconomic status, student gender, parents’ aspirations for their children, mathematics efficacy, and mathematics achievement was tested to examine whether parent involvement in the 10th grade remains relevant to achievement. A sample of data pertaining to 8,673 10th graders from the Educational Longitudinal Study was analyzed. The results indicated that the fit of the measurement model to the data was good (χ2 = 3081.62, df = 87, p = .0, normed fit index [NFI] = .96, comparative fit index [CFI] = .96, root mean square error of approximation [RMSEA] = .064), as was the structural model (χ2 = 3470.69, df = 94, p = .00, NFI = .96, CFI = .96, RMSEA = .065). Although the effect was small in magnitude, parent involvement in advising had a significant indirect relationship with mathematics achievement via mathematics efficacy of 10th graders.  相似文献   

9.
为测试Hewitt多维完美主义量表在中国大学生中的信度和效度,并对其进行修订,对1959名大学生进行测试,采用探索性和验证性因素分析对问卷的因素进行检验,计算量表的内部一致性信度、重测信度等。结果发现量表最后保留15个项目,可解释总方差的49．55％,各维度的项目载荷在0．49～0．77之间。验证性因素分析指标x2、RMSEA、NFI、CFI、CFI分别为796．925、0．075、0．802、0．820、0．835。总量表与分量表的a系数和重测信度都在O．65以上,因此,修订后的HMPS具有较理想的信效度,较适合中国大学生使用。  相似文献   

10.
目的：测试Hewitt多维完美主义量表在中国大学生中的信度、效度,对其进行本土化修订。方法：对523名大学生进行测试,运用探索性和验证性因素分析对量表进行检验,计算量表的内部一致性信度、重测信度等。结果：量表最后保留16个项目,可解释总方差的52．32％,各维度的项目载荷在0．43-0．76之间。验证性因素分析指标RMSEA、NFI、CFI、GFI分别为0．062、0．786、0．891、0．852。总量表与分量表的α系数和重测信度都在0．69以上。结论：修订后的HMPS具有较理想的信效度,较适合中国大学生使用.  相似文献   

11.
Abstract

An increasing number of K–12 schools have adopted blended learning approaches. Current empirical research has been sparse regarding preparing teachers for blended teaching, including the skills they must develop to teach in blended contexts. This research is focused on that weakness, with the purposes of systematically identifying the skills needed for teaching in a blended learning context and of developing and testing an instrument that can be used to determine individual and school-wide readiness for blended teaching. In this study we present a measurement model used to develop items for measuring K–12 blended learning readiness. Specifically the instrument contained the following top-level areas: (a) foundational knowledge, skills, and dispositions, (b) instructional planning, (c) instructional methods and strategies, (d) assessment and evaluation, and (e) management. Each top-level construct also had two to four subconstructs. Through confirmatory factor analysis using survey responses from 2,290?K–12 teachers we found that the data met all four fit statistics cutoffs set forth in the literature (root mean square error of approximation [RMSEA]= 0.041, comparative fit index [CFI]?=?0.926, Tucker–Lewis index [TLI]?=?0.923, standardized root mean square residual [SRMR]?=?0.041, X2?=?978.934, df?=?1992).  相似文献   

12.
Stress research increasingly emphasizes the role of appraisal in determining which events are perceived as stressful. The Classroom Appraisal of Resources and Demands (CARD) was developed to measure teachers’ appraisals of their classroom demands and resources in order to assess their risk for experiencing occupational stress. The present purposes are to review the literature identifying appraisals as a key determinant of stress, to describe the development of the CARD, and to provide meta-analytic results from 18 studies comparing CARD scores to the following variables: teacher’s job satisfaction and occupational commitment, burnout symptoms, stress prevention resources, and challenging student demands. Results suggest moderate effects for associations between the CARD and these constructs, and implications for educational policy aimed at reducing turnover and increasing teacher and student welfare are discussed.  相似文献   

13.
目的：对非学业自我描述量表进行修订和信效度检验.方法：以浙江师范大学492名学生为被试,使用SPSS16.0和Amos5.0进行探索性和验证性因素分析.结果表明：（1）经过探索性因素分析,量表包含7个因子,共45个项目,各个项目负荷在0.416~0.810之间,7个二级因子解释了总方差的54.611%;（2）将7个二级因子按Marsh的多层次自我描述量表依托的理论合并为4个一级因子,提高了内部一致性水平,4个因子及总量表内部一致性系数为0.651~0.821.各因子间相关呈中等偏低相关,结构效度良好;（3）通过验证性因素分析,4个一级因子的模型拟合优度指标分别为：χ2/df〈5,RMSEA〈0.05,GFI,NFI,TLI,CFI为0.989~0.997;（4）在体能、与双亲关系和一般自我3个因子上存在性别的显著性差异,男生比女生评价更积极.鉴于以上结果,非学业自我描述量表的信效度水平达到了测量学的要求.  相似文献   

14.
This article compares two structural equation modeling fit indexes—Bentler's ( 1990; Bentler & Bonett, 1980) Confirmatory Fit Index (CFI) and Steiger and Lind's (1980; Browne & Cudeck, 1993) Root Mean Square Error of Approximation (RMSEA). These two fit indexes are both conceptually linked to the noncentral chi‐square distribution, but CFI has seen much wider use in applied research, whereas RMSEA has only recently been gaining attention. The article suggests that use of CFI is problematic because of its baseline model. CFI seems to be appropriate in more exploratory contexts, whereas RMSEA is appropriate in more confirmatory contexts. On the other hand, CFI does have an established parsimony adjustment, although the adjustment included in RMSEA may be inadequate.  相似文献   

15.
探索积极人格特质问卷(PPTQ)在中国大学生中的因素结构。采用积极人格特质问卷(Positive Personality Traits Questionnaire)中文版,对648名大学生施测,对其中一半数据使用PASWStatistics18进行探索性因素分析,另一半数据使用AMOS16.0进行验证性因素分析(CFA)。探索性因素分析得出积极自我意象、外向性和文化认同三因素结构。累计解释率为50.457%,验证性因素分析结果显示:χ2/df=2.230,GFI=0.841。AGFI=0.816,CFI=0.822,RMSEA=0.062,中文版三因素结构在中国大学生人群中较为合理。  相似文献   

16.
为研究大学生英语课程学习投入情况,编制本问卷并探讨问卷的信度与效度。问卷参考相关成熟问卷,通过课堂观察和开放式问卷等方法收集题项,以西北农林科技大学非英语专业大一、大二学生为调查对象,经预测修订后编制了大学英语课程学习投入问卷。该问卷共含22个题项（其中2题为测谎题）,包含3个维度（认知、情感和行为）;验证性因素分析表明该量表具有较好的拟合指标（χ2/df=2.026, NFI=0.929, NNFI=0.954, CFI=0.960, IFI=0.960, RMR=0.089, RMSEA=0.052）;三维度分问卷信度介于0.836-0.899之间,总问卷信度0.944。可见,该问卷具有良好的信效度,达到测量学的要求,可用于调查学生大学英语课程的学习过程。  相似文献   

17.
工作绩效的四因素结构模型   总被引：18，自引：0，他引：18  
本研究以企业中层管理人员为对象，通过构建工作绩效评定量表，对工作绩效的结构进行了探讨。探索性因素分析表明，工作绩效在结构上可以区分为四个因素：任务绩效、人际绩效、适应绩效和努力绩效；相关分析和多元回归分析表明，构建的量表具有良好的信度和效度。重新采集样本后，经验证性因素分析，发现四因素结构模型有最佳的拟合，从而确认了工作绩效的四因素结构模型。  相似文献   

18.
This study investigated the performance of fit indexes in selecting a covariance structure for longitudinal data. Data were simulated to follow a compound symmetry, first-order autoregressive, first-order moving average, or random-coefficients covariance structure. We examined the ability of the likelihood ratio test (LRT), root mean square error of approximation (RMSEA), comparative fit index (CFI), and Tucker–Lewis Index (TLI) to reject misspecified models with varying degrees of misspecification. With a sample size of 20, RMSEA, CFI, and TLI are high in both Type I and Type II error rates, whereas LRT has a high Type II error rate. With a sample size of 100, these indexes generally have satisfactory performance, but CFI and TLI are affected by a confounding effect of their baseline model. Akaike's Information Criterion (AIC) and Bayesian Information Criterion (BIC) have high success rates in identifying the true model when sample size is 100. A comparison with the mixed model approach indicates that separately modeling the means and covariance structures in structural equation modeling dramatically improves the success rate of AIC and BIC.  相似文献   

19.
Students' perceptions of the education environment influence their learning. Ever since the major medical curriculum reform, anatomy education has undergone several changes in terms of its curriculum, teaching modalities, learning resources, and assessment methods. By measuring students' perceptions concerning anatomy education environment, valuable information can be obtained to facilitate improvements in teaching and learning. Hence, it is important to use a valid inventory that specifically measures attributes of the anatomy education environment. In this study, a new 11‐factor, 132‐items Anatomy Education Environment Measurement Inventory (AEEMI) was developed using Delphi technique and was validated in a Malaysian public medical school. The inventory was found to have satisfactory content evidence (scale‐level content validity index [total] = 0.646); good response process evidence (scale‐level face validity index [total] = 0.867); and acceptable to high internal consistency, with the Raykov composite reliability estimates of the six factors are in the range of 0.604–0.876. The best fit model of the AEEMI is achieved with six domains and 25 items (X2 = 415.67, P < 0.001, ChiSq/df = 1.63, RMSEA = 0.045, GFI = 0.905, CFI = 0.937, NFI = 0.854, TLI = 0.926). Hence, AEEMI was proven to have good psychometric properties, and thus could be used to measure the anatomy education environment in Malaysia. A concerted collaboration should be initiated toward developing a valid universal tool that, using the methods outlined in this study, measures the anatomy education environment across different institutions and countries. Anat Sci Educ 10: 423–432. © 2017 American Association of Anatomists.  相似文献   

20.
The aim of this study was to examine factors that influence Chinese teachers’ attitudes toward using technology. Using the technology acceptance model (TAM) as the framework, the study considered the social and cultural in China, and included a new external variable—policy—along with perceived ease of use, perceived usefulness, facilitation conditions, and subjective norms, into the original TAM framework. Structural equation modeling was implemented on questionnaire data collected from 1,423 teachers in China. The expanded model revealed a goodness-of-fit (TLI = 0.931, CFI = 0.942, RMSEA = 0.048, and SRMR = 0.039) and it explained 52.7% of the variance in teachers’ attitudes toward using technology. Chinese teachers' perceived usefulness, perceived ease of use, and national policy were determined to be the factors with positive direct influence on teachers' attitudes toward using technology. Subjective norms were found to have an indirect influence. This study contributes to the growing body of non-Western multicultural studies on the TAM and also serves as a starting point in understanding teachers’ attitudes toward technology use in China.  相似文献   

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