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1.
Parameter recovery was assessed within mixture confirmatory factor analysis across multiple estimator conditions under different simulated levels of mixture class separation. Mixture class separation was defined in the measurement model (through factor loadings) and the structural model (through factor variances). Maximum likelihood (ML) via the EM algorithm was compared to a Markov chain Monte Carlo (MCMC) estimator condition using weak priors and a condition using tight priors. Results indicated that the MCMC weak condition produced the highest bias, particularly with a weak Dirichlet prior for the mixture class proportions. Specifically, the weak Dirichlet prior affected parameter estimates under all mixture class separation conditions, even with moderate and large sample sizes. With little knowledge about parameters, ML/EM should be used over MCMC weak. However, MCMC tight produced the lowest bias under all mixture class separation conditions and should be used if tight and accurate priors can be placed on parameters.  相似文献   

2.
The aim of this study was to compare the small sample (N = 1, 3, 5, 10, 15) performance of a Bayesian multivariate vector autoregressive (BVAR-SEM) time series model relative to frequentist power and parameter estimation bias. A multivariate autoregressive model was developed based on correlated autoregressive time series vectors of varying lengths (T = 25, 50, 75, 100, 125) using Statistical Analysis System (SAS) version 9.2. Autoregressive components for the 5 series vectors included coefficients of .80, .70, .65, .50 and .40. Error variance components included values of .20, .20, .10, .15, and .15, with cross-lagged coefficients of .10, .10, .15, .10, and .10. A Monte Carlo study revealed that in comparison to frequentist methods, the Bayesian approach provided increased sensitivity for hypothesis testing and detecting Type I error.  相似文献   

3.
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   

4.
The present study explored whether competence beliefs and intrinsic motivation for different school domains show reciprocal effects over time. A sample of 670 German elementary school pupils (M= 8.8 years, SD= 0.51) was followed over 1 year. At 4 measurement occasions, children completed self-reports on their intrinsic motivation and competence beliefs for math, German, and school in general. Latent growth models revealed that intrinsic motivation and competence beliefs decreased over time. Comparing correlational and cross-lagged structural equation models yielded only weak evidence for cross-lagged influences between the 2 constructs. Results suggest that the developmental curves of competence beliefs and intrinsic motivation might be less inextricably interwoven than frequently assumed.  相似文献   

5.
Models of change typically assume longitudinal measurement invariance. Key constructs are often measured by ordered-categorical indicators (e.g., Likert scale items). If tests based on such indicators do not support longitudinal measurement invariance, it would be useful to gauge the practical significance of the detected non-invariance. The authors focus on the commonly used second-order latent growth curve model, proposing a sensitivity analysis that compares the growth parameter estimates from a model assuming the highest achieved level of measurement invariance to those from a model assuming a higher, incorrect level of measurement invariance as a measure of practical significance. A simulation study investigated the practical significance of non-invariance in different locations (loadings, thresholds, uniquenesses) in second-order latent linear growth models. The mean linear slope was affected by non-invariance in the loadings and thresholds, the intercept variance was affected by non-invariance in the uniquenesses, and the linear slope variance and intercept–slope covariance were affected by non-invariance in all three locations.  相似文献   

6.
Semicontinuous variable analysis is a widely appreciated statistical method in such disciplines as social science, medicines, and economics. In detecting underlying structure and representing possible interrelationships, statistical analysis using a two-part model is appropriated. In this paper, we present a general extension of two-part model to the situation where the unobserved factors are included in the two parts to interpret external variability in semicontinuous variable. Auxiliary information on these factors is manifested by continuous responses via measurement model, while the interrelationships among factors are exploited through structural equation model. Moreover, under longitudinal setting, dynamic characteristics of responses between any two occasions are represented by transition model. Procedures for model fitting, parameter estimation, model selection and prediction are developed within the Bayesian paradigm. Markov Chains Monte Carlo method is used to implement posterior analysis. Empirical results including a simulation and a real example are used to illustrate the proposed methodology.  相似文献   

7.
With few exceptions, the dynamics underlying the mood structures of individuals with Parkinson's Disease have consistently been overlooked. Based on 12 participants' daily self-reports over 72 days, we identified 10 participants whose covariance matrices for positive and negative affect were similar enough to warrant pooling. Dynamic factor models that included factor autoregression and cross-regressions were fitted to the pooled, lagged covariance matrix representing approximately 700 occasions of measurement. Although results from the pooled data indicated that both positive and negative affect had a strong lag-1 autoregressive impact on current positive and negative affect, most individuals showed stronger autoregressive effects for positive than negative affect when examined individually. There was also a weak cross-regression effect of positive affect on negative affect, but the reverse was not true. Through model fitting, we demonstrated that failure to incorporate lagged relations among factors could lead to an overestimation of concurrent correlations among latent factors. Implications of the findings in relation to the orthogonality of positive and negative affect are discussed.  相似文献   

8.
This simulation study examined the performance of the curve-of-factors model (COFM) when autocorrelation and growth processes were present in the first-level factor structure. In addition to the standard curve-of factors growth model, 2 new models were examined: one COFM that included a first-order autoregressive autocorrelation parameter, and a second model that included first-order autoregressive and moving average autocorrelation parameters. The results indicated that the estimates of the overall trend in the data were accurate regardless of model specification across most conditions. Variance components estimates were biased across many conditions but improved as sample size and series length increased. In general, the two models that incorporated autocorrelation parameters performed well when sample size and series length were large. The COFM had the best overall performance.  相似文献   

9.
This research focuses on the problem of model selection between the latent change score (LCS) model and the autoregressive cross-lagged (ARCL) model when the goal is to infer the longitudinal relationship between variables. We conducted a large-scale simulation study to (a) investigate the conditions under which these models return statistically (and substantively) different results concerning the presence of bivariate longitudinal relationships, and (b) ascertain the relative performance of an array of model selection procedures when such different results arise. The simulation results show that the primary sources of differences in parameter estimates across models are model parameters related to the slope factor scores in the LCS model (specifically, the correlation between the intercept factor and the slope factor scores) as well as the size of the data (specifically, the number of time points and sample size). Among several model selection procedures, correct selection rates were higher when using model fit indexes (i.e., comparative fit index, root mean square error of approximation) than when using a likelihood ratio test or any of several information criteria (i.e., Akaike’s information criterion, Bayesian information criterion, consistent AIC, and sample-size-adjusted BIC).  相似文献   

10.
This study is designed to test a reciprocal causation, cross-lagged model of self-concept, self-efficacy, and achievement in a postsecondary STEM course. Both self-efficacy and self-concept are known to be related to achievement; however, there is a need to untangle the relationship between the two constructs as well as their association to achievement across time to best direct future research efforts. To achieve this research interest, a longitudinal measurement strategy was used to measure chemistry self-concept and self-efficacy for learning and performance before and after achievement measures (i.e., two term examinations) in a postsecondary organic chemistry course context. A reciprocal causation, cross-lagged model best fits the data as a representation of the relationships between these three measures over time as compared to autoregressive, performance effects, and self-belief effects models. Significant paths in the reciprocal causation, cross-lagged model include the first self-concept measure to the first achievement measure as well as from the second self-concept measure to the third self-efficacy measure. Relationships from achievement to each subsequent self-belief measure were also significant. This study demonstrates the ability of longitudinal measurements of multiple constructs in postsecondary STEM educational research to collect nuanced information that is overlooked when pre-measure designs of single constructs are used. In the classroom, an initial measure of self-concept can inform instructors of the likelihood of students to succeed on an initial achievement measure, at which point they may choose to implement some of the targeted intervention strategies from literature.  相似文献   

11.
This study reports relationships between general academic self-concept and achievement in grade 3 and grade 5. Gender-specific effects were investigated using a longitudinal, two-cycle, 3-year autoregressive cross-lagged panel design in a large, representative sample of Polish primary school pupils (N?=?4226). Analysis revealed (a) reciprocal relations between general academic self-concept and achievement over time but the influence of prior achievement on self-concept was stronger; (b) on average, levels of both constructs declined over time; (c) gender differences were not observed in longitudinal relations (i.e. cross-lagged, autoregressive and intra-wave correlations); (d) girls demonstrated higher mean levels of academic achievement at both grades; and (e) average level of general academic self-concept was not gender differentiated in grade 3 but decreased more for girls. These results are discussed in the light of the theoretical and practical implications.  相似文献   

12.

The aim of the study is to investigate the measurement invariance of mathematics self-concept and self-efficacy across 40 countries that participated in the Programme for International Student Assessment (PISA) 2003 and 2012 cycles. The sample of the study consists of 271,760 students in PISA 2003 and 333,804 students in PISA 2012. Firstly, the traditional measurement invariance testing was applied in the multiple-group confirmatory factor analysis (MGCFA). Then, the alignment analyses were performed, allowing non-invariance to a minimum to estimate all of the parameters. Results from MGCFA indicate that mathematics self-concept and self-efficacy hold metric invariance across the 80 groups (cycle by country). The alignment method results suggest that a large proportion of non-invariance exists in both mathematics self-concept and self-efficacy factors, and the factor means cannot be compared across all participating countries. Results of the Monte Carlo simulation show that the alignment results are trustworthy. Implications and limitations are discussed, and some recommendations for future research are proposed.

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13.
This study tested a structural equation model of enrollment patterns of white and Hispanic males and females in two-year institutions and the invariance of parameter estimates among the different subgroups in the study. The model represented a multiequation model with three latent endogenous variables, high school academic preparation in mathematics and science, mathematics and science attitudes, and the dependent variable, enrollment patterns in mathematics and science courses. Exogenous variables included parents' education, levels of encouragement by others, and high school grades. Structural equation modeling was used to examine the structural and measurement coefficients of the hypothesized causal model for all subgroups in the study. In summary, an examination of the direct and total effect coefficients revealed different underlying patterns of factors for white and Hispanic females. No convergence on the model was found for white and Hispanic males. Equality constraints on all structural coefficients for both white and Hispanic females were tested and results indicated that all parameter estimates in the structural models for both subgroups were significantly different from each other.  相似文献   

14.
Minor cross-loadings on non-targeted factors are often found in psychological or other instruments. Forcing them to zero in confirmatory factor analyses (CFA) leads to biased estimates and distorted structures. Alternatively, exploratory structural equation modeling (ESEM) and Bayesian structural equation modeling (BSEM) have been proposed. In this research, we compared the performance of the traditional independent-clusters-confirmatory-factor-analysis (ICM-CFA), the nonstandard CFA, ESEM with the Geomin- or Target-rotations, and BSEMs with different cross-loading priors (correct; small- or large-variance priors with zero mean) using simulated data with cross-loadings. Four factors were considered: the number of factors, the size of factor correlations, the cross-loading mean, and the loading variance. Results indicated that ICM-CFA performed the worst. ESEMs were generally superior to CFAs but inferior to BSEM with correct priors that provided the precise estimation. BSEM with large- or small-variance priors performed similarly while the prior mean for cross-loadings was more important than the prior variance.  相似文献   

15.
This study examined temperament dimensions of emotion as precursors of children's social information processing (SIP) of stressful peer events. Two hundred and forty-three preschool children (M = 4.60 years) and their primary caregivers participated in two measurement occasions spaced 2 years apart. Observations of temperamental anger, fearful distress, positive affect, and effortful control were assessed in multiple laboratory tasks across two visits at Wave 1. SIP assessments from vignettes of peer challenges were repeated across two waves and included: eye tracking measures of attention to peer emotion displays, hostile attribution bias, hostile solutions, and subjective distress. Findings from structural equation models with inclusion of autoregressive controls indicated that effortful control, fear, and anger predicted subsequent changes in specific SIP dimensions.  相似文献   

16.
This study examined the relationship between intellectual development and identity from the beginning of the student's freshman year in college to the end of the sophomore year. Hierarchical structural equation modeling was performed on the data utilizing LISREL VI. The optimal structural model included significant positive longitudinal paths from time one to time two for both intellectual development and identity. In addition, the cross-lagged path from identity to intellectual development was significant and positive. The results of this investigation suggest that one's sense of identity as a college freshman plays an important role in his or her intellectual development at the end of the sophomore year. Results for intervention possibilities and further research are discussed.  相似文献   

17.
In this study, we investigate the meaning students attribute to the structure of mathematical induction (MI) and the process of proof construction using mathematical induction in the context of a geometric recursion problem. Two hundred and thirteen 17-year-old students of an upper secondary school in Greece participated in the study. Students’ responses in 3 written tasks and the interviews with 18 of them are analyzed. Though MI is treated operationally in school, the students, when challenged, started to recognize the structural characteristics of MI. In the case of proof construction, we identified 2 types of transition from argumentation to proof, interwoven in the structure of the geometrical pattern. In the first type, MI was applied to the algebraic statement that derived from the direct translation of the geometrical situation. In the second type, MI was embedded functionally in the geometrical structure of the pattern.  相似文献   

18.
A multilevel meta-analysis can combine the results of several single-subject experimental design studies. However, the estimated effects are biased if the effect sizes are standardized and the number of measurement occasions is small. In this study, the authors investigated 4 approaches to correct for this bias. First, the standardized effect sizes are adjusted using Hedges’ small sample bias correction. Next, the within-subject standard deviation is estimated by a 2-level model per study or by using a regression model with the subjects identified using dummy predictor variables. The effect sizes are corrected using an iterative raw data parametric bootstrap procedure. The results indicate that the first and last approach succeed in reducing the bias of the fixed effects estimates. Given the difference in complexity, we recommend the first approach.  相似文献   

19.
This study tests a model of reciprocal influences between absenteeism and youth psychopathology using 3 longitudinal datasets (Ns = 20,745, 2,311, and 671). Participants in 1st through 12th grades were interviewed annually or biannually. Measures of psychopathology include self-, parent-, and teacher-report questionnaires. Structural cross-lagged regression models were tested. In a nationally representative data set (Add Health), middle school students with relatively greater absenteeism at Study Year 1 tended toward increased depression and conduct problems in Study Year 2, over and above the effects of autoregressive associations and demographic covariates. The opposite direction of effects was found for both middle and high school students. Analyses with 2 regionally representative data sets were also partially supportive. Longitudinal links were more evident in adolescence than in childhood.  相似文献   

20.
Recently, advancements in Bayesian structural equation modeling (SEM), particularly software developments, have allowed researchers to more easily employ it in data analysis. With the potential for greater use, come opportunities to apply Bayesian SEM in a wider array of situations, including for small sample size problems. Effective use of Bayseian estimation hinges on selection of appropriate prior distributions for model parameters. Researchers have suggested that informative priors may be useful with small samples, presuming that the mean of the prior is accurate with respect to the population mean. The purpose of this simulation study was to examine model parameter estimation for the Multiple Indicator Multiple Cause model when an informative prior distribution had an incorrect mean. Results demonstrated that the use of incorrect informative priors with somewhat larger variance than is typical, yields more accurate parameter estimates than do naïve priors, or maximum likelihood estimation. Implications for practice are discussed.  相似文献   

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