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1.
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
2.
Bayesian methods have the potential for increasing power in mediation analysis (Koopman, Howe, Hollenbeck, & Sin, 2015; Yuan & MacKinnon, 2009). This article compares the power of Bayesian credibility intervals for the mediated effect to the power of normal theory, distribution of the product, percentile, and bias-corrected bootstrap confidence intervals at N ≤ 200. Bayesian methods with diffuse priors have power comparable to the distribution of the product and bootstrap methods, and Bayesian methods with informative priors had the most power. Varying degrees of precision of prior distributions were also examined. Increased precision led to greater power only when N ≥ 100 and the effects were small, N < 60 and the effects were large, and N < 200 and the effects were medium. An empirical example from psychology illustrated a Bayesian analysis of the single mediator model from prior selection to interpreting results. 相似文献
3.
Most accounts of affect and motivation in the science education literature have discussed them as relevant to, but distinct from, disciplinary pursuits. These include Pintrich’s seminal work on affective and motivational factors in learning science (P. R. Pintrich, 1999, 2003; P. R. Pintrich & E. De Groot, 1990; P. R. Pintrich, R. W. Marx, & R. A. Boyle, 1993). Our purpose here is to build on those ideas, drawing as well on accounts of scientists’ practices (e.g., H. E. Gruber, 1974; E. F. Keller, 1983) and of students’ taking up of disciplinary pursuits (R. A. Engle & F. R. Conant, 2002; R. Lehrer, 2009; M. Scardamalia & C. Bereiter, 1991, 2006) to propose that affect and motivation are inherent in the disciplinary practices of science. Thus, we introduce notions of epistemic affect and epistemic motivation, and we illustrate how these are evident in a case study of a student we have followed from 4th to 7th grade. We consider how this perspective aligns with and contributes to research on interest (e.g., S. Hidi, 2006; S. Hidi, K. A. Renninger, & A. Krapp, 2004; C. Sansone, 2009), and we discuss implications for research and instruction in science education. We argue that part of what should happen in the science class is to cultivate students’ feelings and motivations within the discipline. 相似文献
4.
Stochastic differential equation (SDE) models are a promising method for modeling intraindividual change and variability. Applications of SDEs in the social sciences are relatively limited, as these models present conceptual and programming challenges. This article presents a novel method for conceptualizing SDEs. This method uses structural equation modeling (SEM) conventions to simplify SDE specification, the flexibility of SEM to expand the range of SDEs that can be fit, and SEM diagram conventions to facilitate the teaching of SDE concepts. This method is a variation of latent difference scores (McArdle, 2009; McArdle & Hamagami, 2001) and the oversampling approach (Singer, 2012), and approximates the advantages of analytic methods such as the exact discrete model (Oud & Jansen, 2000) while retaining the modeling fiexibility of methods such as latent differential equation modeling (Boker, Neale, & Rausch, 2004). A simulation and empirical example are presented to illustrate that this method can be implemented on current computing hardware, produces good approximations of analytic solutions, and can flexibly accommodate novel models. 相似文献
5.
Julie Gess-Newsome Joseph A. Taylor Janet Carlson April L. Gardner Christopher D. Wilson Molly A. M. Stuhlsatz 《International Journal of Science Education》2019,41(7):944-963
ABSTRACTIn this exploratory study, we attempted to measure potential changes in teacher knowledge and practice as a result of an intervention, as well as trace such changes through a theoretical path of influence that could inform a model of teacher professional knowledge. We created an instrument to measure pedagogical content knowledge (PCK), studied the impact of a two-year professional development intervention, explored the relationships among teacher variables to attempt to validate a model of teacher professional knowledge, and examined the relationship of teacher professional knowledge and classroom practice on student achievement. Teacher professional knowledge and skill was measured in terms of academic content knowledge (ACK), general pedagogical knowledge (GenPK), PCK and teacher practice. Our PCK instrument identified two factors within PCK: PCK-content knowledge and PCK-pedagogical knowledge. Teacher gains existed for all variables. Only GenPK had a significant relationship to teacher practice. ACK was the only variable that explained a substantial portion of student achievement. Our findings provide empirical evidence that we interpret through the lens of the model of teacher professional knowledge and skill, including PCK [Gess-Newsome, J. (2015). A model of teacher professional knowledge and skill including PCK: Results of the thinking from the PCK summit. In A. Berry, P. Friedrichsen, & J. Loughran (Eds.), Re-examining pedagogical content knowledge in science education (pp. 28–42). London: Routledge Press], highlighting the complexity of measuring teacher professional knowledge and skill. 相似文献
6.
Yuan and Hayashi (2010) introduced 2 scatter plots for model and data diagnostics in structural equation modeling (SEM). However, the generation of the plots requires in-depth understanding of their underlying technical details. This article develops and introduces an R package semdiag for easily drawing the 2 plots. With a model specified in EQS syntax, one only needs to supply as few as 2 parameters to generate the 2 plots using the semdiag package. Two examples are provided to illustrate the use of the package. Multiple figures are used to explain the elements of data and model diagnostics. Advice on selecting proper estimation methods following the diagnostics is also given. 相似文献
7.
Both ad-hoc robust sandwich standard error estimators (design-based approach) and multilevel analysis (model-based approach) are commonly used for analyzing complex survey data with nonindependent observations. Although these 2 approaches perform equally well on analyzing complex survey data with equal between- and within-level model structures (B. O. Muthén & Satorra, 1995), the performances of these 2 approaches for analyzing multilevel data with unequal between- and within-level structures have not yet been systematically examined. In this study, we extended B. O. Muthén and Satorra's (1995) study by comparing these 2 approaches and an additional model-based maximum model for analyzing multilevel data considering number of clusters, cluster size, intraclass correlation, and the equality of different level structures. The simulation results showed the model-based maximum model generally performed well across conditions. This model is also recommended as an alternative for analyzing nonindependent survey data, especially when the information of the higher level model structure is not known. 相似文献
8.
First-order latent growth curve models (FGMs) estimate change based on a single observed variable and are widely used in longitudinal research. Despite significant advantages, second-order latent growth curve models (SGMs), which use multiple indicators, are rarely used in practice, and not all aspects of these models are widely understood. In this article, our goal is to contribute to a better understanding of theoretical and practical differences between FGMs and SGMs. We define the latent variables in FGMs and SGMs explicitly on the basis of latent state–trait (LST) theory and discuss insights that arise from this approach. We show that FGMs imply a strict trait-like conception of the construct under study, whereas SGMs allow for both trait and state components. Based on a simulation study and empirical applications to the Center for Epidemiological Studies Depression Scale (Radloff, 1977) we illustrate that, as an important practical consequence, FGMs yield biased reliability estimates whenever constructs contain state components, whereas reliability estimates based on SGMs were found to be accurate. Implications of the state–trait distinction for the measurement of change via latent growth curve models are discussed. 相似文献
9.
Craig K. Enders 《Structural equation modeling》2013,20(3):434-448
Recent missing data studies have argued in favor of an “inclusive analytic strategy” that incorporates auxiliary variables into the estimation routine, and Graham (2003) outlined methods for incorporating auxiliary variables into structural equation analyses. In practice, the auxiliary variables often have missing values, so it is reasonable to ask whether the inclusion of such variables will improve the estimation of model parameters. Simulation results indicated that the proportion of missing data and the missing data mechanism of the auxiliary variables had little impact on bias. Even when an auxiliary variable was missing not at random, bias was relegated to the auxiliary variable portion of the model, and did not propagate into the model of substantive interest. The study results suggest that the inclusion of an auxiliary variable is beneficial, even if the auxiliary variable has a substantial proportion of missing data. 相似文献
10.
School policy on teaching and the school learning environment (SLE) are the main school factors of the dynamic model of educational effectiveness (Creemers & Kyriakides, 2008). A longitudinal study in which 50 primary schools, 108 classes, and 2369 students participated generated evidence supporting the validity of the dynamic model. This article reports the results of a re-analysis of the data of this study in order to search for direct and indirect effects of school factors included in the model. Using multilevel structural equation modelling techniques, indirect effects of school policy on teaching and SLE upon achievement in mathematics and Greek language are demonstrated. Implications of findings are drawn. Comparing the results of the multilevel direct and indirect effect model with those from using a multilevel regression model, we demonstrate the importance of choosing appropriate conceptual models and using relevant methodological approaches to understand the dynamic nature of educational effectiveness. 相似文献
11.
The primary goal of this article is to demonstrate the close relationship between 2 classes of dynamic models in psychological research: latent change score models and continuous time models. The secondary goal is to point out some differences. We begin with a brief review of both approaches, before demonstrating how the 2 methods are mathematically and conceptually related. It will be shown that most commonly used latent change score models are related to continuous time models by the difference equation approximation to the differential equation. One way in which the 2 approaches differ is the treatment of time. Whereas there are theoretical and practical restrictions regarding observation time points and intervals in latent change score models, no such limitations exist in continuous time models. We illustrate our arguments with three simulated data sets using a univariate and bivariate model with equal and unequal time intervals. As a by-product of this comparison, we discuss the use of phantom and definition variables to account for varying time intervals in latent change score models. We end with a reanalysis of the Bradway–McArdle longitudinal study on intellectual abilities (used before by McArdle & Hamagami, 2004) by means of the proportional change score model and the dual change score model in discrete and continuous time. 相似文献
12.
Within the past decade, the achievement goal approach has begun to be used to study teacher achievement motivation. In recent research with students, a 3 × 2 model of achievement goals has been proffered that separates mastery-based goals in terms of a task/self distinction. The purpose of the present study was to extend this 3 × 2 model to teachers in order to provide important insights into teachers’ individual differences. We devised items for the questionnaire and showed that data obtained with the 3 × 2 Achievement Goal Questionnaire for Teachers fit the 3 × 2 model (in absolute terms and relative to 10 alternative models) and that each goal of the model exhibited good internal consistency. In addition, we linked the 3 × 2 goals to other key constructs relevant to achievement goals, namely, implicit theories of ability, instructional practices and intrinsic interest. 相似文献
13.
It is difficult for busy health care providers to perform routine screening for older women's posttraumatic stress symptomatology. This difficulty is due, at least partially, to a paucity of instruments specifically tested on such a population. To address this issue, in this preliminary study we tested an abbreviated screen from the set of 20 items comprising the Distressing Event Questionnaire (DEQ; Kubany, Leisen, Kaplan, & Kelly, 2000a) on a convenience sample of 94 ethnically diverse older women (age 52–105). This new five-item derivation, named Brief Posttraumatic Stress Screening Scale (BPSSS), assesses posttraumatic stress based on the Diagnostic and Statistical Manual of Mental Disorders (DSM–IV; American Psychiatric Association, 1994). Its conciseness reduces the likelihood that older women would become fatigued during assessment, making it ideal for use in busy health care settings. In view of the hypothesized cohesiveness of the tool's five items, we expected the screen to be reliable. Because the BPSSS has only five items, a single factor was hypothesized to account for a large proportion of the variance in its items. We also expected that scores on the screen would correlate (to a certain extent) with those on measures of depression and perceived stress of a nontraumatic and nonmedical nature. A standardized alpha of .86 demonstrated high internal consistency of the BPSSS, and the exploratory factor analysis showed that one factor accounted for 58% of the five items' variance. Moreover, the correlations of BPSSS scores with scores on nontraumatic stress and depression were moderate yet significant (r = .37, p < .01 and r = .50, p < .01, respectively). 相似文献
14.
ABSTRACTThis paper concludes the Special Issue (SI) ‘Probing the Amalgam: the relationship between science teachers’ content, pedagogical and pedagogical content knowledge’. We review the five papers (Sorge et al; Gess-Newsome et al; Kind; Pitjeng-Mosabala and Rollnick; and Liepertz and Bronowski) by discussing evidence these present regarding the relationships between content knowledge (CK), pedagogical knowledge (PK) and pedagogical content knowledge (PCK); the development of CK, PK and PCK in novice and experienced secondary science teachers and how CK, PK and/or PCK impact students’ learning. In conclusion, we draw these findings together in offering proposals for future research via reconsideration of Shulman’s amalgam. This includes post-hoc examination of a PCK model known as ‘the Consensus Model’ (Gess-Newsome, [2015]. A model of teacher professional knowledge and skill including PCK: Results of the thinking from the PCK Summit. In A. Berry, P. J. Friedrichsen, & J. Loughran (Eds.), Re-examining Pedagogical Content Knowledge in Science Education (pp. 28–42). New York, NY: Routledge; Neumann, Kind, & Harms [2018]. Probing the amalgam: The relationship between science teachers’ content, pedagogical and pedagogical content knowledge. International Journal of Science Education, 1–15) and presentation of a novel PCK structure based on evidence from the SI studies. 相似文献
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16.
A broad literature seeks to assess the importance of schools, proxies for school quality, and family background on children's achievement growth using the education production function. Using rich data from the Philippines, we introduce and estimate a model that imposes little structure on the relationship between intake achievement and follow-up achievement and evaluate school performance based on this estimated relationship. Our methods nest typical value-added specifications that use test score gains as the outcome variable and models assuming linearity in the relationship between intake and follow-up scores. We find evidence against the use of value-added models for our data and show that such models give very different assessments of school performance in the Philippines. Using a variety of tests we find that schools matter in the production of student achievement, though variation in performance across schools only explains about 4.4–5.3% of the total (conditional) variation in follow-up achievement. Schools providing basic facilities—in particular schools providing electricity—are found to perform much better in the production of achievement growth. 相似文献
17.
This article reports on the South African results of a study to identify and explain relationships between some major factors associated with successful reading at Grade 5. With 11 official languages, educational policy in South Africa advocates an additive bilingualism model, and students in Grades 1 to 3 are taught in their mother tongue. Thereafter, the language of learning and teaching changes to a second language, which in most cases is English. With this complexity of issues, hierarchical linear modeling (HLM) was used to determine the effect of a number of explanatory variables at student and school level on reading achievement as outcome variable, while controlling for language using the South African Progress in International Reading Literacy Study (PIRLS) 2006 data. Utilizing Creemers' comprehensive model of educational effectiveness (Creemers & Reezigt, 1999) as theoretical point of departure, this article will focus on the results of an overall South African model with student- and school-level variables. 相似文献
18.
Peter A.M. Scheltinga Hans Kuyper Anneke C. Timmermans Greetje P.C. van der Werf 《教育心理学》2016,36(7):1173-1195
The dominant achievement goals (DAGs) of 7008 students in the third grade of Dutch secondary education (US grade 9) were investigated, based on Elliot & McGregors’ 2 × 2 framework (2001), in relation to track-level and motivational variables. We found the mastery-approach goal and the performance-approach goal, generally considered adaptive, to be more prominent among students in lower tracks. In contrast, avoidance goals were more common in higher tracks. Most notably, in the highest track, the mastery-avoidance goal was the most prominent. Additionally, we found that students with a dominant performance-approach goal scored highest on almost all motivational variables examined; students without a DAG scored mostly second highest. The implications of these findings are discussed. 相似文献
19.
Ana Kozina 《Educational studies》2015,41(1-2):109-121
In this study, we analyse the predictive power of home and school environment-related factors for determining pupils’ aggression. The multiple regression analyses are performed for fourth- and eighth-grade pupils based on the Trends in Mathematics and Science Study (TIMSS) 2007 (N = 8394) and TIMSS 2011 (N = 9415) databases for Slovenia. At the national level, the Lestvica agresivnosti aggression scale was administered in both TIMSS cycles. For home environment variables, we included those related to socio-economic status, pupils’ educational aspirations, parental activities with their children and pupils’ free time activities. The results show that the variables related to socio-economic status, spare time activities and parental activities are significant predictors. The results differ in both analysed data-sets. For school environment variables, we include those related to the school climate, pupils’ attitudes towards school and school subjects and pupils’ achievement in mathematics. We find that the variables related to school climate and students’ self-confidence are significant predictors. These results are stable in both years. The predictive power of the school characteristics model (including only the school environment variables) is larger (based on the proportion of explained variance) compared with the home characteristics model. The hierarchical linear model of data from 2007 to 2011 shows small differences in aggression between schools. The inclusion of two data cycles collected in two time- periods allows us to observe changes in aggression predictors over time. Practical implications are finally included. 相似文献
20.
Interim tests are a central component of district-wide assessment systems, yet their technical quality to guide decisions (e.g., instructional) has been repeatedly questioned. In response, the study purpose was to investigate the validity of a series of English Language Arts (ELA) interim assessments in terms of dimensionality and prediction of summative test performance, based on Grade 6 student data (N = 4,651) from a larger, urban district. Factor analytic results supported modeling the interim test data in terms of a bifactor model (Gibbons & Hedeker, 1992), with items reporting moderate to high relationships to the primary dimension (i.e., ELA) and varying estimates on the secondary domains. Hierarchical multiple linear regression results indicated that primary ELA scores were the strongest predictors of summative test performance, with subscale scores not improving predictive accuracy. Findings address issues pertaining to investigating the technical quality of test data widely used in district-wide assessment systems. 相似文献