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1.
Popular longitudinal models allow for prediction of growth trajectories in alternative ways. In latent class growth models (LCGMs), person-level covariates predict membership in discrete latent classes that each holistically define an entire trajectory of change (e.g., a high-stable class vs. late-onset class vs. moderate-desisting class). In random coefficient growth models (RCGMs, also known as latent curve models), however, person-level covariates separately predict continuously distributed latent growth factors (e.g., an intercept vs. slope factor). This article first explains how complex and nonlinear interactions between predictors and time are recovered in different ways via LCGM versus RCGM specifications. Then a simulation comparison illustrates that, aside from some modest efficiency differences, such predictor relationships can be recovered approximately equally well by either model—regardless of which model generated the data. Our results also provide an empirical rationale for integrating findings about prediction of individual change across LCGMs and RCGMs in practice. 相似文献
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《Structural equation modeling》2013,20(1):59-72
A non-arbitrary method for the identification and scale setting of latent variables in general structural equation modeling is introduced. This particular technique provides identical model fit as traditional methods (e.g., the marker variable method), but it allows one to estimate the latent parameters in a nonarbitrary metric that reflects the metric of the measured indicators. This technique, therefore, is particularly useful for mean and covariance structures (MACS) analyses, where the means of the indicators and latent constructs are of key interest. By introducing this alternative method of identification and scale setting, researchers are provided with an additional tool for conducting MACS analyses that provides a meaningful and nonarbitrary scale for the estimates of the latent variable parameters. Importantly, this tool can be used with single-group single-occasion models as well as with multiple-group models, multiple-occasion models, or both. 相似文献
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If the factor structure of a test does not hold over time (i.e., is not invariant), then longitudinal comparisons of standing on the test are not meaningful. In the case of the Wechsler Intelligence Scale for Children‐Third Edition (WISC‐III), it is crucial that it exhibit longitudinal factorial invariance because it is widely used in high‐stakes special education eligibility decisions. Accordingly, the present study analyzed the longitudinal factor structure of the WISC‐III for both configural and metric invariance with a group of 177 students with disabilities tested, on average, 2.8 years apart. Equivalent factor loadings, factor variances, and factor covariances across the retest interval provided evidence of configural and metric invariance. It was concluded that the WISC‐III was measuring the same constructs with equal fidelity across time which allows unequivocal interpretation of score differences as reflecting changes in underlying latent constructs rather than variations in the measurement operation itself. © 2001 John Wiley & Sons, Inc. 相似文献
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This article examines the problem of specification error in 2 models for categorical latent variables; the latent class model and the latent Markov model. Specification error in the latent class model focuses on the impact of incorrectly specifying the number of latent classes of the categorical latent variable on measures of model adequacy as well as sample reallocation to latent classes. The results show that the clarity of remaining latent classes, as measured by the entropy statistic depends on the number of observations in the omitted latent class—but this statistic is not reliable. Specification error in the latent Markov model focuses on the transition probabilities when a longitudinal Guttman process is incorrectly specified. The findings show that specifying a longitudinal Guttman process that is not true in the population impacts other transition probabilities through the covariance matrix of the logit parameters used to calculate those probabilities. 相似文献
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AbstractTrait–State–Occasion (TSO) covariance models represent an important advance in methods for studying the longitudinal stability of latent constructs. Such models have only been examined under fairly restricted conditions (e.g., having only 2 tau-equivalent indicators per wave). In this study, Monte Carlo simulations revealed the effects of having 2 versus 3 indicators per wave and relaxing the within-wave tau equivalence. These modifications were examined under conditions that varied with regard to the within-wave trait variance and the cross-wave stability of occasion influences. In general, the TSO model performed well (i.e., few convergence problems or out-of-range parameter estimates) under most of these conditions; however, the likelihood of improper solutions increased when only 2 indicators were used per wave, when factor loadings were small, when the proportion of trait variance was either very high or very low, and when the occasion factor was highly stable. Based on these findings, recommendations are made for successful use of TSO models with real data. 相似文献
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The inclusion of a representative sample of understudied populations (e.g., women, minorities, older adults, youth, and people with disabilities) in physical activity promotion studies is a public health priority. Given the limited empirical evidence of effective recruitment strategies and limitations in research methodology for both over represented and understudied populations, the purpose of this paper was to overview the effectiveness of different recruitment techniques derived from active and/or passive approaches among mainly under represented populations. Additionally, recommendations for effective recruitment methods are proposed considering such factors as demographic characteristics and target population. Effective recruitment methodology among all people—regardless of age, ethnic background, functional level, or gender—is important for determining the generalizability of study findings. 相似文献
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Elizabeth Bettini Yujeong Park Amber Benedict Jenna Kimerling Walter Leite 《Exceptionality》2016,24(3):176-193
This investigation examined relationships among special education teachers’ working conditions (e.g., classroom characteristics, administrative support), personal characteristics (e.g., experience, certification status, self-efficacy), instructional quality, and students with disabilities’ reading achievement and behavioral outcomes. Data from the 2004–2005 administration of the Special Education Elementary Longitudinal Study were used. Confirmatory factor analysis was used to test the fit of models for five latent factors. Hybrid structural models were applied to test the hypothesis that working conditions would be positively associated with special education teachers’ self-efficacy and their instructional quality, which would, in turn, be positively associated with their students’ reading achievement and behavioral outcomes. Although the initial structural equation model tested failed to support the hypotheses, several significant relationships with theoretical and practical significance were discovered. Directions for future research and practical implications are discussed. 相似文献
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Yoonjeong Kang 《Journal of Experimental Education》2017,85(3):376-388
Structured means analysis is a very useful approach for testing hypotheses about population means on latent constructs. In such models, a z test is most commonly used for testing the statistical significance of the relevant parameter estimates or of the differences between parameter estimates, where a z value is computed based on the asymptotic standard error estimate associated with the parameter of interest. In the current article, a series of population analyses demonstrate that the z tests for latent mean structure parameters or, more directly, the standard error estimates upon which those z tests are based are, not invariant to how factors are scaled. As such, circumstances exist in which latent mean inference is compromised solely as a result of scaling decisions. This problem is illustrated in the context of between-subjects (i.e., multisample) latent means models and within-subjects latent means models. Recommendations for practice are also offered. 相似文献
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Jason M. Prenoveau 《Structural equation modeling》2016,23(5):731-749
Latent state–trait models are valuable tools for representing the longitudinal stability and variability of individuals’ relative standing on a construct (e.g., a behavior or psychological process). Specifically, state–trait models partition construct variance into time-varying and time-invariant components, enabling one to examine the relations between these components and other variables. Such partitioning of construct variance has a number of valuable applications including the improvement of risk-outcome research. The trait–state–occasion (TSO) model and latent state–trait model with autoregression (LST–AR) are ideal for use with constructs with relative stability that decreases with increasing durations, but relative stability that does not decrease to 0 even over long durations. Despite the fact that this pattern of relative stability expression is observed for a wide variety of constructs, there are relatively few applications of the TSO and LST–AR models. Thus, this article describes the TSO and LST–AR models and illustrates application of these models. 相似文献
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Measurement bias can be detected using structural equation modeling (SEM), by testing measurement invariance with multigroup factor analysis (Jöreskog, 1971;Meredith, 1993;Sörbom, 1974) MIMIC modeling (Muthén, 1989) or restricted factor analysis (Oort, 1992,1998). In educational research, data often have a nested, multilevel structure, for example when data are collected from children in classrooms. Multilevel structures might complicate measurement bias research. In 2-level data, the potentially “biasing trait” or “violator” can be a Level 1 variable (e.g., pupil sex), or a Level 2 variable (e.g., teacher sex). One can also test measurement invariance with respect to the clustering variable (e.g., classroom). This article provides a stepwise approach for the detection of measurement bias with respect to these 3 types of violators. This approach works from Level 1 upward, so the final model accounts for all bias and substantive findings at both levels. The 5 proposed steps are illustrated with data of teacher–child relationships. 相似文献
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The first years on the job are very challenging for teachers (e.g., Fives, Hamman, & Olivarez, 2007; Goddard, O’Brien, & Goddard, 2006). Two of the main challenges are to learn to regulate the highly complex classroom situations (Jones, 2006) and to regulate their own emotional resources (Chang, 2009). Accordingly, in the present study, we investigated changes in teacher candidates’ classroom management knowledge as well as emotional exhaustion at the beginning of their teaching careers. We applied latent change models to a sample of 746 teacher candidates who were assessed twice during the German induction phase (the Referendariat). We found evidence for a significant increase in teacher candidates’ classroom management knowledge during the induction phase. Emotional exhaustion increased during the first year and decreased during the second year of the induction phase. We also investigated between-person differences in the changes. Classroom management knowledge was predicted by the teacher candidates’ cognitive personal characteristics (e.g., cognitive abilities and willingness to reflect), whereas emotional exhaustion was predicted by noncognitive personal characteristics (e.g., emotional stability) as well as variables related to the induction phase (e.g., perceived mentoring quality and teaching load). Classroom management knowledge and emotional exhaustion were only modestly associated. 相似文献
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Karyn Riddle 《Communication quarterly》2013,61(4):446-462
Prior research suggests violent narratives can transport viewers, affecting attitudes and beliefs. This research project explores whether a factor related to a media text —vividness—affects the degree to which audience members become transported into a violent narrative. Furthermore, this study focuses on the various subcomponents of the transportation experience (e.g., attention, emotional involvement, and mental imagery processes) to see if vividness affects some components more than others. In an experiment, 179 participants were exposed to vivid or non-vivid versions of violent television programs. Findings reveal that viewers of vivid violence exhibited stronger emotional reactions and higher attention levels. Vividness did not impact mental imagery processes or excitation levels, however. Implications for transportation, vividness, and media violence research are discussed. 相似文献
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《Structural equation modeling》2013,20(4):493-530
Recent developments in finite mixture modeling allow for the identification of different developmental processes in distinct but unobserved subgroups within a population. The new approach, described within the general growth mixture modeling framework (Muthen, 2001, in press), extends conventional random coefficient growth models to incorporate a categorical latent trajectory variable representing latent classes or mixtures (i.e., the subgroups in the population whose membership must be inferred from the data). This article provides a didactic example of this new methodology with adolescent alcohol use data, which is shown to consist of a mixture of distinct subgroups, defined by unique growth trajectories and differing predictors and sequelae. The method is discussed as a useful tool for mapping hypotheses of development onto appropriate statistical models. 相似文献
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In psychological, social, behavioral, and medical studies, hidden Markov models (HMMs) have been extensively applied to the simultaneous modeling of heterogeneous observation and hidden transition in the analysis of longitudinal data. However, the majority of the existing HMMs are developed in a parametric framework without latent variables. This study considers a novel semiparametric HMM, which comprises a semiparametric latent variable model to investigate the complex interrelationships among latent variables and a nonparametric transition model to examine the linear and nonlinear effects of potential predictors on hidden transition. The Bayesian P-splines approach and Markov chain Monte Carlo methods are developed to estimate the unknown, a Bayesian model comparison statistic, is employed to conduct model comparison. The empirical performance of the proposed methodology is evaluated through simulation studies. An application to a data set derived from the National Longitudinal Survey of Youth is presented. 相似文献
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We consider a multivariate generalized latent variable model to investigate the effects of observable and latent explanatory variables on multiple responses of interest. Various types of correlated responses, such as continuous, count, ordinal, and nominal variables, are considered in the regression. A generalized confirmatory factor analysis model that is capable of managing mixed-type data is proposed to characterize latent variables via correlated observed indicators. In addressing the complicated structure of the proposed model, we introduce continuous underlying measurements to provide a unified model framework for mixed-type data. We develop a multivariate version of the Bayesian adaptive least absolute shrinkage and selection operator procedure, which is implemented with a Markov chain Monte Carlo (MCMC) algorithm in a full Bayesian context, to simultaneously conduct estimation and model selection. The empirical performance of the proposed methodology is demonstrated through a simulation study. An application of the proposed method to a study of adolescent substance abuse based on the National Longitudinal Survey of Youth is presented. 相似文献
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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
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Michele Vecchione Guido Alessandri Gian Vittorio Caprara John Tisak 《Structural equation modeling》2013,20(1):117-130
This research investigated the nature of the method effect associated with positively worded items of the Life Orientation Test–Revised. In a first cross-sectional study (N?=?11,028) the best fitting model posits 2 factors, representing general optimism and a specific factor associated with positive items. In a second longitudinal study (N?=?203), a unified latent curve latent state–trait model was used to assess the developmental trajectory of the specific factor from 16 to 20 years. This factor contains a prevalence of trait versus state variance, and presents a relationship pattern with external criteria (e.g., depression) that differ from the one involving general optimism. 相似文献
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Carlos J. Álvarez Marcus Taft Juan A. Hernández-Cabrera 《Scientific Studies of Reading》2017,21(2):99-108
A word-spotting task is used in Spanish to test the way in which polysyllabic letter-strings are parsed in this language. Monosyllabic words (e.g., bar) embedded at the beginning of a pseudoword were immediately followed by either a coda-forming consonant (e.g., barto) or a vowel (e.g., baros). In the former case, the embedded word corresponds to the first spoken syllable, whereas it cuts across the syllable boundary in the latter case. Unlike a previous study in English using the same methodology (Taft & Álvarez, 2014), the embedded word was found to be easier to detect when followed by a consonant than a vowel, at least for low-frequency words. It was concluded that phonological recoding is more important in the parsing of Spanish words than English words, where maximization of the coda dominates instead. 相似文献