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1.
The alignment method (Asparouhov & Muthén, 2014) is an alternative to multiple-group factor analysis for estimating measurement models and testing for measurement invariance across groups. Simulation studies evaluating the performance of the alignment for estimating measurement models across groups show promising results for continuous indicators. This simulation study builds on previous research by investigating the performance of the alignment method’s measurement models estimates with polytomous indicators under conditions of systematically increasing, partial measurement invariance. We also present an evaluation of the testing procedure, which has not been the focus of previous simulation studies. Results indicate that the alignment adequately recovers parameter estimates under small and moderate amounts of noninvariance, with issues only arising in extreme conditions. In addition, the statistical tests of invariance were fairly conservative, and had less power for items with more extreme skew. We include recommendations for using the alignment method based on these results. 相似文献
2.
Yutian T. Thompson Hairong Song Dexin Shi Zhengkui Liu 《Educational and psychological measurement》2021,81(1):5
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. 相似文献
3.
Confirmatory factor analytic tests of measurement invariance (MI) require a referent indicator (RI) for model identification. Although the assumption that the RI is perfectly invariant across groups is acknowledged as problematic, the literature provides relatively little guidance for researchers to identify the conditions under which the practice is appropriate. Using simulated data, this study examined the effects of RI selection on both scale- and item-level MI tests. Results indicated that while inappropriate RI selection has little effect on the accuracy of conclusions drawn from scale-level tests of metric invariance, poor RI choice can produce very misleading results for item-level tests. As a result, group comparisons under conditions of partial invariance are highly susceptible to problems associated with poor RI choice. 相似文献
4.
Socioeconomic status (SES) is often used as control variable when relations between academic outcomes and students' migrational background are investigated. When measuring SES, indicators used must have the same meaning across groups. This study aims to examine the measurement invariance of SES, using data from TIMSS, 2003. The study shows that a latent SES variable has the same meaning across sub-populations with Swedish and non-Swedish background. However, the assumption of scalar invariance was rejected, which is essential for estimation of differences in latent means between groups. Comparisons between models assuming different degrees of scalar invariance indicated that models allowing partial scalar invariance should not be used when comparing latent variable means across groups of students with different migrational backgrounds. 相似文献
5.
This work aimed to test the invariance of a causal structural model of the determinants of academic achievement in underachieving and non-underachieving students. A theoretical model of the relationships between personal, social, and familial variables and academic performance was derived empirically using data from a large sample obtained in a previous study, prior to testing for invariance across the two student groups. Underachieving students were identified using the Rasch model procedure. The sample comprised 259 underachieving and 258 non-underachieving students. The latter were selected randomly from a large non-underachieving sample of Spanish secondary education students. For model comparisons between groups, multiple-group causal structural analyses were performed, following a sequence of nested models with increasing constraints. The results showed a good fit of the model in both groups, although about half of the parameters were not invariant across groups. Underachieving students were characterized by their lack of learning strategies, an academic self-concept that exerted less influence on achievement, and a positive effect of the parent-school relationship on academic performance/achievement. Non-underachieving students were characterized by their use of metacognitive strategies, which led to higher academic achievement, a greater effect of self-concept on their achievement, the perception of parental support leading to higher performance, and the positive effects of peer acceptance on academic achievement. 相似文献
6.
Although much is known about the performance of recent methods for inference and interval estimation for indirect or mediated effects with observed variables, little is known about their performance in latent variable models. This article presents an extensive Monte Carlo study of 11 different leading or popular methods adapted to structural equation models with latent variables. Manipulated variables included sample size, number of indicators per latent variable, internal consistency per set of indicators, and 16 different path combinations between latent variables. Results indicate that some popular or previously recommended methods, such as the bias-corrected bootstrap and asymptotic standard errors had poorly calibrated Type I error and coverage rates in some conditions. Likelihood-based confidence intervals, the distribution of the product method, and the percentile bootstrap emerged as leading methods for both interval estimation and inference, whereas joint significance tests and the partial posterior method performed well for inference. 相似文献
7.
This article used the Wald test to evaluate the item‐level fit of a saturated cognitive diagnosis model (CDM) relative to the fits of the reduced models it subsumes. A simulation study was carried out to examine the Type I error and power of the Wald test in the context of the G‐DINA model. Results show that when the sample size is small and a larger number of attributes are required, the Type I error rate of the Wald test for the DINA and DINO models can be higher than the nominal significance levels, while the Type I error rate of the A‐CDM is closer to the nominal significance levels. However, with larger sample sizes, the Type I error rates for the three models are closer to the nominal significance levels. In addition, the Wald test has excellent statistical power to detect when the true underlying model is none of the reduced models examined even for relatively small sample sizes. The performance of the Wald test was also examined with real data. With an increasing number of CDMs from which to choose, this article provides an important contribution toward advancing the use of CDMs in practical educational settings. 相似文献
8.
Symeon P. Vlachopoulos 《Structural equation modeling》2013,20(1):114-135
This study examined the extent of measurement invariance of the Basic Psychological Needs in Exercise Scale responses (BPNES; Vlachopoulos & Michailidou, 2006) across male (n = 716) and female (n = 1,147) exercise participants. BPNES responses from exercise participants attending private fitness centers (n = 1,012) and community exercise programs (n = 851) were used. The 3-factor BPNES confirmatory factor analysis model, discriminant validity, and scale reliability were supported for both male and female participants separately. The multisample models supported the configural invariance, partial metric invariance, partial measurement error invariance, and partial scalar invariance of the BPNES responses across gender. Both male and female participants attached the same meaning to the constructs assessed by the BPNES items. The BPNES score invariance properties support tests of the needs universality hypothesis offered by self-determination theory across gender in exercise and meaningful comparison of the autonomy, competence, and relatedness construct latent means across gender. 相似文献
9.
Yan Wang Eunsook Kim John M. Ferron Robert F. Dedrick Tony X. Tan Stephen Stark 《Educational and psychological measurement》2021,81(1):61
Factor mixture modeling (FMM) has been increasingly used to investigate unobserved population heterogeneity. This study examined the issue of covariate effects with FMM in the context of measurement invariance testing. Specifically, the impact of excluding and misspecifying covariate effects on measurement invariance testing and class enumeration was investigated via Monte Carlo simulations. Data were generated based on FMM models with (1) a zero covariate effect, (2) a covariate effect on the latent class variable, and (3) covariate effects on both the latent class variable and the factor. For each population model, different analysis models that excluded or misspecified covariate effects were fitted. Results highlighted the importance of including proper covariates in measurement invariance testing and evidenced the utility of a model comparison approach in searching for the correct specification of covariate effects and the level of measurement invariance. This approach was demonstrated using an empirical data set. Implications for methodological and applied research are discussed. 相似文献
10.
Detecting Differential Item Discrimination (DID) and the Consequences of Ignoring DID in Multilevel Item Response Models 
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下载免费PDF全文 Cross‐level invariance in a multilevel item response model can be investigated by testing whether the within‐level item discriminations are equal to the between‐level item discriminations. Testing the cross‐level invariance assumption is important to understand constructs in multilevel data. However, in most multilevel item response model applications, the cross‐level invariance is assumed without testing of the cross‐level invariance assumption. In this study, the detection methods of differential item discrimination (DID) over levels and the consequences of ignoring DID are illustrated and discussed with the use of multilevel item response models. Simulation results showed that the likelihood ratio test (LRT) performed well in detecting global DID at the test level when some portion of the items exhibited DID. At the item level, the Akaike information criterion (AIC), the sample‐size adjusted Bayesian information criterion (saBIC), LRT, and Wald test showed a satisfactory rejection rate (>.8) when some portion of the items exhibited DID and the items had lower intraclass correlations (or higher DID magnitudes). When DID was ignored, the accuracy of the item discrimination estimates and standard errors was mainly problematic. Implications of the findings and limitations are discussed. 相似文献
11.
Multigroup confirmatory factor analysis (MCFA) is a popular method for the examination of measurement invariance and specifically, factor invariance. Recent research has begun to focus on using MCFA to detect invariance for test items. MCFA requires certain parameters (e.g., factor loadings) to be constrained for model identification, which are assumed to be invariant across groups, and act as referent variables. When this invariance assumption is violated, location of the parameters that actually differ across groups becomes difficult. The factor ratio test and the stepwise partitioning procedure in combination have been suggested as methods to locate invariant referents, and appear to perform favorably with real data examples. However, the procedures have not been evaluated through simulations where the extent and magnitude of a lack of invariance is known. This simulation study examines these methods in terms of accuracy (i.e., true positive and false positive rates) of identifying invariant referent variables. 相似文献
12.
In this study, we present a thermal optimization method using the overall lumped parameter (LP) and partial computational fluid dynamics (CFD) modeling for a 600-kW permanent magnet traction motor developed for high-speed trains. The motor is totally enclosed forced ventilated to achieve high power density, high efficiency, and low maintenance requirements. Considering the electro-magnetic performance, bogie space, and thermal capacity, we propose a ventilation structure with zigzag plates in sector cross-section. We focus particularly on the ventilation channels and propose an overall LP model for thermal optimization, in which the full consideration of the influence of turbulent flow is given by using a partial CFD model. Given the specific critical parameters from the optimization results, we present a complete 3D CFD model of the whole motor to obtain an accurate temperature distribution and the maximum temperature rises in local points. The benefit of zigzag plates is studied extensively using both the LP and the complete CFD models and the results are verified by equivalent thermal experiments under rated operations. Experimental results indicate that the ventilation structure fulfills the normal operational demands of high-speed trains by improving thermal performance by more than 15%. Additionally, we propose an engineering method to estimate iron loss constraint with the complete CFD model to guide the control system design. 相似文献
13.
In testing factorial invariance, researchers have often used a reference variable strategy in which the factor loading for a variable (i.e., reference variable) is fixed to 1 for identification. This commonly used method can be misleading if the chosen reference variable is actually a noninvariant item. This simulation study suggests an alternative method for testing factorial invariance and evaluates the performance of the method in specification searches based on the modification index. The results of the study showed that the proposed specification searches performed well when the number of noninvariant variables was relatively small and this performance improved as sample size increased and the size of group differences increased. When the number of noninvariant variables was relatively large, however, the method rarely succeeded in detecting the noninvariant items in the specification searches. Implications of the findings are discussed along with the limitations of the study. 相似文献
14.
Analyzing examinees’ responses using cognitive diagnostic models (CDMs) has the advantage of providing diagnostic information. To ensure the validity of the results from these models, differential item functioning (DIF) in CDMs needs to be investigated. In this article, the Wald test is proposed to examine DIF in the context of CDMs. This study explored the effectiveness of the Wald test in detecting both uniform and nonuniform DIF in the DINA model through a simulation study. Results of this study suggest that for relatively discriminating items, the Wald test had Type I error rates close to the nominal level. Moreover, its viability was underscored by the medium to high power rates for most investigated DIF types when DIF size was large. Furthermore, the performance of the Wald test in detecting uniform DIF was compared to that of the traditional Mantel‐Haenszel (MH) and SIBTEST procedures. The results of the comparison study showed that the Wald test was comparable to or outperformed the MH and SIBTEST procedures. Finally, the strengths and limitations of the proposed method and suggestions for future studies are discussed. 相似文献
15.
A Note on the Invariance of the DINA Model Parameters 总被引：1，自引：0，他引：1
Cognitive diagnosis models (CDMs), as alternative approaches to unidimensional item response models, have received increasing attention in recent years. CDMs are developed for the purpose of identifying the mastery or nonmastery of multiple fine-grained attributes or skills required for solving problems in a domain. For CDMs to receive wider use, researchers and practitioners need to understand the basic properties of these models. The article focuses on one CDM, the deterministic inputs, noisy "and" gate (DINA) model, and the invariance property of its parameters. Using simulated data involving different attribute distributions, the article demonstrates that the DINA model parameters are absolutely invariant when the model perfectly fits the data. An additional example involving different ability groups illustrates how noise in real data can contribute to the lack of invariance in these parameters. Some practical implications of these findings are discussed . 相似文献
16.
When factorial invariance is violated, a possible first step in locating the source of violation(s) might be to pursue partial factorial invariance (PFI). Two commonly used methods for PFI are sequential use of the modification index (backward MI method) and the factor-ratio test. In this study, we propose a simple forward method using the confidence interval (forward CI method). We compare the performances of the aforementioned 3 methods under various simulated PFI conditions. Results indicate that the forward CI method using 99% CIs has the highest perfect recovery rates and the lowest Type I error rates. A performance that is competitive with this is that produced by the backward method with the more conservative criterion (MI = 6.635). Consistently delivering the poorest performance, regardless of the chosen confidence level, was the factor-ratio test. Also discussed are the work’s contribution, implications, and limitations. 相似文献
17.
环上的自由模是域上线性空间的一种推广，因而线性空间的许多性质可以自然地推广到环上的自由模．文[1]指出，交换环上自由模的基所含元素的个数是自由模的一个不变量，即基元个数不变性．这里对任意环上自由模的基及相关矩阵进行了讨论，给出了任意环上两个自由模R^（m）与R^（n）同构的充要条件，R^（m），R^（n）分别是秩为m，n的自由R-模，并且Hom（R^（m），R^（n））是秩为mn的自由R-模，同时做出了使R^（m）≌R^（n）、但m=n不成立的反例． 相似文献
18.
基于跨时测量恒等视角与知识图谱分析,文章对我国教育技术学较常探讨的变量"自我效能"量表进行了工具检测,并以四川省某小学三年级的197名学生为被试,前后测时间间隔为6个月。文章采用结构方程模型的跨时测量恒等检验程序,依序针对不同恒等程度的模型进行比较,结果发现:数学自我效能量表不符合完全的度量恒等,放宽两道题项的参数限制后可达到部分的纯量恒等,但仍不及严格恒等的要求;跨时测量恒等性的结果会影响配对样本t检验的结论。基于此,文章提出建议:为了提升实验的内在效度,较长时间的实验研究应纳入工具的跨时测量恒等性检验。 相似文献
19.
Several structural equation modeling (SEM) strategies were developed for assessing measurement invariance (MI) across groups relaxing the assumptions of strict MI to partial, approximate, and partial approximate MI. Nonetheless, applied researchers still do not know if and under what conditions these strategies might provide results that allow for valid comparisons across groups in large-scale comparative surveys. We perform a comprehensive Monte Carlo simulation study to assess the conditions under which various SEM methods are appropriate to estimate latent means and path coefficients and their differences across groups. We find that while SEM path coefficients are relatively robust to violations of full MI and can be rather effectively recovered, recovering latent means and their group rankings might be difficult. Our results suggest that, contrary to some previous recommendations, partial invariance may rather effectively recover both path coefficients and latent means even when the majority of items are noninvariant. Although it is more difficult to recover latent means using approximate and partial approximate MI methods, it is possible under specific conditions and using appropriate models. These models also have the advantage of providing accurate standard errors. Alignment is recommended for recovering latent means in cases where there are only a few noninvariant parameters across groups. 相似文献
20.
Zijun Ke 《Structural equation modeling》2013,20(3):382-400
This study examined and compared various statistical methods for detecting individual differences in change. Considering 3 issues including test forms (specific vs. generalized), estimation procedures (constrained vs. unconstrained), and nonnormality, we evaluated 4 variance tests including the specific Wald variance test, the generalized Wald variance test, the specific likelihood ratio (LR) variance test, and the generalized LR variance test under both constrained and unconstrained estimation for both normal and nonnormal data. For the constrained estimation procedure, both the mixture distribution approach and the alpha correction approach were evaluated for their performance in dealing with the boundary problem. To deal with the nonnormality issue, we used the sandwich standard error (SE) estimator for the Wald tests and the Satorra–Bentler scaling correction for the LR tests. Simulation results revealed that testing a variance parameter and the associated covariances (generalized) had higher power than testing the variance solely (specific), unless the true covariances were zero. In addition, the variance tests under constrained estimation outperformed those under unconstrained estimation in terms of higher empirical power and better control of Type I error rates. Among all the studied tests, for both normal and nonnormal data, the robust generalized LR and Wald variance tests with the constrained estimation procedure were generally more powerful and had better Type I error rates for testing variance components than the other tests. Results from the comparisons between specific and generalized variance tests and between constrained and unconstrained estimation were discussed. 相似文献