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1.
The analysis of interaction among latent variables has received much attention. This article introduces a Bayesian approach to analyze a general structural equation model that accommodates the general nonlinear terms of latent variables and covariates. This approach produces a Bayesian estimate that has the same statistical optimal properties as a maximum likelihood estimate. Other advantages over the traditional approaches are discussed. More important, we demonstrate through examples how to use the freely available software WinBUGS to obtain Bayesian results for estimation and model comparison. Simulation studies are conducted to assess the empirical performances of the approach for situations with various sample sizes and prior inputs. 相似文献
2.
Assessing Fit of Unidimensional Item Response Theory Models Using a Bayesian Approach 总被引：1，自引：0，他引：1
Sandip Sinharay 《Journal of Educational Measurement》2005,42(4):375-394
Even though Bayesian estimation has recently become quite popular in item response theory (IRT), there is a lack of works on model checking from a Bayesian perspective. This paper applies the posterior predictive model checking (PPMC) method ( Guttman, 1967 ; Rubin, 1984 ), a popular Bayesian model checking tool, to a number of real applications of unidimensional IRT models. The applications demonstrate how to exploit the flexibility of the posterior predictive checks to meet the need of the researcher. This paper also examines practical consequences of misfit, an area often ignored in educational measurement literature while assessing model fit. 相似文献
3.
An approach called generalizability in item response modeling (GIRM) is introduced in this article. The GIRM approach essentially incorporates the sampling model of generalizability theory (GT) into the scaling model of item response theory (IRT) by making distributional assumptions about the relevant measurement facets. By specifying a random effects measurement model, and taking advantage of the flexibility of Markov Chain Monte Carlo (MCMC) estimation methods, it becomes possible to estimate GT variance components simultaneously with traditional IRT parameters. It is shown how GT and IRT can be linked together, in the context of a single-facet measurement design with binary items. Using both simulated and empirical data with the software WinBUGS, the GIRM approach is shown to produce results comparable to those from a standard GT analysis, while also producing results from a random effects IRT model. 相似文献
4.
Drawing valid inferences from modern measurement models is contingent upon a good fit of the data to the model. Violations of model‐data fit have numerous consequences, limiting the usefulness and applicability of the model. As Bayesian estimation is becoming more common, understanding the Bayesian approaches for evaluating model‐data fit models is critical. In this instructional module, Allison Ames and Aaron Myers provide an overview of Posterior Predictive Model Checking (PPMC), the most common Bayesian model‐data fit approach. Specifically, they review the conceptual foundation of Bayesian inference as well as PPMC and walk through the computational steps of PPMC using real‐life data examples from simple linear regression and item response theory analysis. They provide guidance for how to interpret PPMC results and discuss how to implement PPMC for other model(s) and data. The digital module contains sample data, SAS code, diagnostic quiz questions, data‐based activities, curated resources, and a glossary. 相似文献
5.
Structural equation models are widely appreciated in behavioral, social, and psychological research to model relations between latent constructs and manifest variables, and to control for measurement errors. Most applications of structural equation models are based on fully observed data that are independently distributed. However, hierarchical data with a correlated structure are common in behavioral research, and very often, missing data are encountered. In this article, we propose a 2-level structural equation model for analyzing hierarchical data with missing entries, and describe a Bayesian approach for estimation and model comparison. We show how to use WinBUGS software to get the solution conveniently. The proposed methodologies are illustrated through a simulation study, and a real application in relation to organizational and management research concerning the study of the interrelationships of the latent constructs about job satisfaction, job responsibility, and life satisfaction for citizens in 43 countries. 相似文献
6.
Conventionally, moderated mediation analysis is conducted through adding relevant interaction terms into a mediation model of interest. In this study, we illustrate how to conduct moderated mediation analysis by directly modeling the relation between the indirect effect components including a and b and the moderators, to permit easier specification and interpretation of moderated mediation. With this idea, we introduce a general moderated mediation model that can be used to model many different moderated mediation scenarios including the scenarios described in Preacher, Rucker, and Hayes (2007). Then we discuss how to estimate and test the conditional indirect effects and to test whether a mediation effect is moderated using Bayesian approaches. How to implement the estimation in both BUGS and Mplus is also discussed. Performance of Bayesian methods is evaluated and compared to that of frequentist methods including maximum likelihood (ML) with 1st-order and 2nd-order delta method standard errors and mL with bootstrap (percentile or bias-corrected confidence intervals) via a simulation study. The results show that Bayesian methods with diffuse (vague) priors implemented in both BUGS and Mplus yielded unbiased estimates, higher power than the ML methods with delta method standard errors, and the ML method with bootstrap percentile confidence intervals, and comparable power to the ML method with bootstrap bias-corrected confidence intervals. We also illustrate the application of these methods with the real data example used in Preacher et al. (2007). Advantages and limitations of applying Bayesian methods to moderated mediation analysis are also discussed. 相似文献
7.
Bayesian methods incorporate model parameter information prior to data collection. Eliciting information from content experts is an option, but has seen little implementation in Bayesian item response theory (IRT) modeling. This study aims to use ethical reasoning content experts to elicit prior information and incorporate this information into Markov Chain Monte Carlo (MCMC) estimation. A six‐step elicitation approach is followed, with relevant details at each stage for two IRT items parameters: difficulty and guessing. Results indicate that using content experts is the preferred approach, rather than noninformative priors, for both parameter types. The use of a noninformative prior for small samples provided dramatically different results when compared to results from content expert–elicited priors. The WAMBS (When to worry and how to Avoid the Misuse of Bayesian Statistics) checklist is used to aid in comparisons. 相似文献
8.
Most of the software that is available to implement Bayesian approaches uses Markov chain Monte Carlo (MCMC) methods. It is our impression that many researchers are primarily concerned with convergence as assessed by the Potential Scale Reduction (PSR) and that other aspects of MCMC are largely ignored. In this article, we argue that the precision with which the Bayesian estimates are approximated by summary statistics for the MCMC chain is essential to ensure good statistical properties. We discuss the Effective Sample Size (ESS), which indicates how well an estimate is approximated, and present evidence from two simulation studies and an example from organizational research to support our claim that researchers should be concerned not only with convergence but also with precision, particularly when a multilevel model is estimated. In addition, we demonstrate how Mplus can be modified so that users can control the ESS, and we conclude with recommendations. 相似文献
9.
Model selection is important in any statistical analysis, and the primary goal is to find the preferred (or most parsimonious) model, based on certain criteria, from a set of candidate models given data. Several recent publications have employed the deviance information criterion (DIC) to do model selection among different forms of multilevel item response theory models (MLIRT). The majority of the practitioners use WinBUGS for implementing MCMC algorithms for MLIRT models, and the default version of DIC provided by WinBUGS focused on the measurement‐level parameters only. The results herein show that this version of DIC is inappropriate. This study introduces five variants of DIC as a model selection index for MLIRT models with dichotomous outcomes. Considering a multilevel IRT model with three levels, five forms of DIC are formed: first‐level conditional DIC computed from the measurement model only, which is the index given by many software packages such as WinBUGS; second‐level marginalized DIC and second‐level joint DIC computed from the second‐level model; and top‐level marginalized DIC and top‐level joint DIC computed from the entire model. We evaluate the performance of the five model selection indices via simulation studies. The manipulated factors include the number of groups, the number of second‐level covariates, the number of top‐level covariates, and the types of measurement models (one‐parameter vs. two‐parameter). Considering the computational viability and interpretability, the second‐level joint DIC is recommended for MLIRT models under our simulated conditions. 相似文献
10.
Dynamic structural equation modeling (DSEM) is a novel, intensive longitudinal data (ILD) analysis framework. DSEM models intraindividual changes over time on Level 1 and allows the parameters of these processes to vary across individuals on Level 2 using random effects. DSEM merges time series, structural equation, multilevel, and time-varying effects models. Despite the well-known properties of these analysis areas by themselves, it is unclear how their sample size requirements and recommendations transfer to the DSEM framework. This article presents the results of a simulation study that examines the estimation quality of univariate 2-level autoregressive models of order 1, AR(1), using Bayesian analysis in Mplus Version 8. Three features are varied in the simulations: complexity of the model, number of subjects, and number of time points per subject. Samples with many subjects and few time points are shown to perform substantially better than samples with few subjects and many time points. 相似文献
11.
公共政策制定是公共政策执行的前提。政策执行作为政策运行过程的中间环节,是将政策从理念转化为现实的过程,是政策成败的关键。现阶段我国地方政府还存在不同程度的政策执行偏差问题。究其根源,主要在于地方政府部门、政府官员本身也是具有特殊利益取向的自利性主体。因此,从政府自利的角度出发,深入探讨地方政府政策执行偏差的原因,对于规范地方政府的行为、保障公共政策的有效执行乃至提高政府的公信力和执行力,都具有理论意义和现实意义。 相似文献
12.
Multilevel Structural equation models are most often estimated from a frequentist framework via maximum likelihood. However, as shown in this article, frequentist results are not always accurate. Alternatively, one can apply a Bayesian approach using Markov chain Monte Carlo estimation methods. This simulation study compared estimation quality using Bayesian and frequentist approaches in the context of a multilevel latent covariate model. Continuous and dichotomous variables were examined because it is not yet known how different types of outcomes—most notably categorical—affect parameter recovery in this modeling context. Within the Bayesian estimation framework, the impact of diffuse, weakly informative, and informative prior distributions were compared. Findings indicated that Bayesian estimation may be used to overcome convergence problems and improve parameter estimate bias. Results highlight the differences in estimation quality between dichotomous and continuous variable models and the importance of prior distribution choice for cluster-level random effects. 相似文献
13.
Rens van de Schoot David Kaplan Jaap Denissen Jens B. Asendorpf Franz J. Neyer Marcel A.G. van Aken 《Child development》2014,85(3):842-860
Bayesian statistical methods are becoming ever more popular in applied and fundamental research. In this study a gentle introduction to Bayesian analysis is provided. It is shown under what circumstances it is attractive to use Bayesian estimation, and how to interpret properly the results. First, the ingredients underlying Bayesian methods are introduced using a simplified example. Thereafter, the advantages and pitfalls of the specification of prior knowledge are discussed. To illustrate Bayesian methods explained in this study, in a second example a series of studies that examine the theoretical framework of dynamic interactionism are considered. In the Discussion the advantages and disadvantages of using Bayesian statistics are reviewed, and guidelines on how to report on Bayesian statistics are provided. 相似文献
14.
Hilary Dack 《The Teacher Educator》2019,54(1):22-45
While teacher education programs are expected to teach effective methods of differentiating instruction, limited research to date has examined the meaning-making processes through which candidates build an understanding of this complex philosophy of teaching and learning. Drawing upon activity theory, this interpretive qualitative study examined how candidates’ understandings of differentiation's conceptual and practical tools—and their concerns about its implementation–changed as they encountered accurate, in-depth information about the model in a course on differentiation. Data sources included interviews, assignments, and observations. Findings suggested candidates entered the course with common misconceptions about differentiation's conceptual tools. Although many candidates originally conceptualized differentiation as a set of practical tools, they later viewed it as a conceptual framework that guides practice. As candidates appropriated practical tools of differentiation, common concerns about implementing differentiation diminished. Implications include questions teacher educators who teach candidates about differentiation should pose to guide their own instruction. 相似文献
15.
Gilda Segal 《Research in Science Education》1997,27(2):289-307
This paper contrasts naive beliefs about the nature of science, with science as it appears from sociological and philosophical
study, feminist critique and insights from multicultural education. I draw implications from these informed views to suggest
how school science might be modified to project a pragmatic view of science to its students that allows students to know science
and its relationships to themselves and society in multi-faceted ways. From these perspectives, pragmatic school science is
situated within a values framework that questions how we know. Pragmatic school science also requires that the naive inductivist
views that permeate school science inquiry methods at present be modified to recognise that observations and inquiry are guided
by prior knowledge and values; that new knowledge is tentative; that some knowledge has high status, as it has been constructed
consensually over a long period; but that even high status knowledge can be challenged. For implementation of these reforms,
yet still to embrace the need for some students to appropriate understanding of discipline knowledge required for advanced
science education, a broad set of aims is required. 相似文献
16.
睡眠呼吸暂停综合征 (SleepApneaSyndromes,SAS) ,表现为在睡眠中反复出现暂时性呼吸停止 ,每晚 7h左右睡眠中 ,呼吸暂停可达 30次以上且每次在 10s以上。目前常用多导睡眠仪或呼吸诊断仪通过临床监护进行诊断 ,但是价格昂贵复杂 ,不便推广。本文在详述该征及诊断同时还介绍了一种简便易行的检测SAS的有效方法 ,即利用人在呼吸时鼻腔周围的温度和压力变化 ,通过换能器来获得睡眠中的呼吸信息 ,利用运放构成简单电路 ,用计算器作计数器组成简易呼吸暂停检测装置。 相似文献
17.
This article presents relevant research on Bayesian methods and their major applications to modeling in an effort to lay out differences between the frequentist and Bayesian paradigms and to look at the practical implications of these differences. Before research is reviewed, basic tenets and methods of the Bayesian approach to modeling are presented and contrasted with basic estimation results from a frequentist perspective. It is argued that Bayesian methods have become a viable alternative to traditional maximum likelihood-based estimation techniques and may be the only solution for more complex psychometric data structures. Hence, neither the applied nor the theoretical measurement community can afford to neglect the exciting new possibilities that have opened up on the psychometric horizon. 相似文献
18.
This article is based on a survey carried out at Imperial College, to understand better needs, problems, advantages/disadvantages and solutions in the use of new technologies in a specific context, such as engineering education. In comparison with other research on this matter, perceptions, benefits and barriers to using computer-assisted learning and information and communication technologies in higher education, the present study reveals something more about the use of educational technologies in scientific subjects: many lecturers believe that technical subjects do appear to benefit greatly from the ability to teach using real-life computer simulations which help with student motivation and understanding. Moreover, the use of computers allows practical experiences and help in data analysis, and often work would be impossible without computers. Nevertheless, the survey results indicate that, although there are many advantages in the use of computers in teaching and learning, there are many difficulties for lecturers in using the new technologies because of logistical problems, such as lack of time, technical support, appropriate software and hardware, etc. There is a need to consider what support can be offered and how, on a national level. 相似文献
19.
Aeneas Rooch Philipp Junker Jörg Härterich Klaus Hackl 《European Journal of Engineering Education》2016,41(2):172-191
Too difficult, too abstract, too theoretical – many first-year engineering students complain about their mathematics courses. The project MathePraxis aims to resolve this disaffection. It links mathematical methods as they are taught in the first semesters with practical problems from engineering applications – and thereby shall give first-year engineering students a vivid and convincing impression of where they will need mathematics in their later working life. But since real applications usually require more than basic mathematics and first-year engineering students typically are not experienced with construction, mensuration and the use of engineering software, such an approach is hard to realise. In this article, we show that it is possible. We report on the implementation of MathePraxis at Ruhr-Universität Bochum. We describe the set-up and the implementation of a course on designing a mass damper which combines basic mathematical techniques with an impressive experiment. In an accompanying evaluation, we have examined the students' motivation relating to mathematics. This opens up new perspectives how to address the need for a more practically oriented mathematical education in engineering sciences. 相似文献
20.
Modeling Diagnostic Assessments with Bayesian Networks 总被引：1，自引：0，他引：1
Russell G. Almond Louis V. DiBello Brad Moulder Juan-Diego Zapata-Rivera 《Journal of Educational Measurement》2007,44(4):341-359
This paper defines Bayesian network models and examines their applications to IRT-based cognitive diagnostic modeling. These models are especially suited to building inference engines designed to be synchronous with the finer grained student models that arise in skills diagnostic assessment. Aspects of the theory and use of Bayesian network models are reviewed, as they affect applications to diagnostic assessment. The paper discusses how Bayesian network models are set up with expert information, improved and calibrated from data, and deployed as evidence-based inference engines. Aimed at a general educational measurement audience, the paper illustrates the flexibility and capabilities of Bayesian networks through a series of concrete examples, and without extensive technical detail. Examples are provided of proficiency spaces with direct dependencies among proficiency nodes, and of customized evidence models for complex tasks. This paper is intended to motivate educational measurement practitioners to learn more about Bayesian networks from the research literature, to acquire readily available Bayesian network software, to perform studies with real and simulated data sets, and to look for opportunities in educational settings that may benefit from diagnostic assessment fueled by Bayesian network modeling. 相似文献