共查询到20条相似文献，搜索用时 15 毫秒
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《Contemporary educational psychology》2005,30(1):81-95
Standardized testing has been implemented in most school districts as part of an effort to improve student achievement in mathematics, reading, science, and English. There have been heated debates as to the effects of these improvement efforts on student achievement. In studying these issues, it is important to examine longitudinal growth patterns for individuals. In most of the studies, however, there is a lack of empirical data at the individual student level or the studies are cross-sectional in nature. The current study attempts to examine growth patterns of student math achievement between 1997 and 2000 and individual differences in growth patterns. MDS exploratory growth modeling was used in the investigation based on data from 716 students in a single school district. Individual differences in growth rates were found. Disadvantaged (limited English proficiency and special education) students had lower initial achievement levels and did not seem to be catching up to other students because their average growth rates were similar to those of other students. These results are discussed in light of recent school reform efforts and the goal of closing achievement gaps. 相似文献
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This report uses structural equation modeling to combine traditional ideas from repeated-measures ANOVA with some traditional ideas from longitudinal factor analysis. A longitudinal model that includes correlations, variances, and means is described as a latent growth curve model (LGM). When merged with repeated-measures data, this technique permits the estimation of parameters representing both individual and group dynamics. The statistical basis of this model allows hypothesis testing of various developmental ideas, including models of alternative dynamic functions and models of the sources of individual differences in these functions. Aspects of these latent growth models are illustrated with a set of longitudinal WISC data from young children and by using the LISREL V computer program. 相似文献
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Tenko Raykov 《Structural equation modeling》2013,20(3):212-236
This article utilizes structural equation modeling for purposes of simultaneous study of individual and group latent change patterns on several longitudinally assessed variables. The approach is based on a special case of the comprehensive latent curve analysis by Meredith and Tisak (1990). Substantively interesting aspects of individual and group growth curves, as well as the interrelations among their patterns, are parameterized at the latent ability level. The method is illustrated on data from a two‐group study by Baltes, Dittmann‐Kohli, and Kliegl (1986). 相似文献
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This study proposes a structured constructs model (SCM) to examine measurement in the context of a multidimensional learning progression (LP). The LP is assumed to have features that go beyond a typical multidimentional IRT model, in that there are hypothesized to be certain cross‐dimensional linkages that correspond to requirements between the levels of the different dimensions. The new model builds on multidimensional item response theory models and change‐point analysis to add cut‐score and discontinuity parameters that embody these substantive requirements. This modeling strategy allows us to place the examinees in the appropriate LP level and simultaneously to model the hypothesized requirement relations. Results from a simulation study indicate that the proposed change‐point SCM recovers the generating parameters well. When the hypothesized requirement relations are ignored, the model fit tends to become worse, and the model parameters appear to be more biased. Moreover, the proposed model can be used to find validity evidence to support or disprove initial theoretical hypothesized links in the LP through empirical data. We illustrate the technique with data from an assessment system designed to measure student progress in a middle‐school statistics and modeling curriculum. 相似文献
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David B. Flora Patrick J. Curran Andrea M. Hussong Michael C. Edwards 《Structural equation modeling》2013,20(4):676-704
A large literature emphasizes the importance of testing for measurement equivalence in scales that may be used as observed variables in structural equation modeling applications. When the same construct is measured across more than one developmental period, as in a longitudinal study, it can be especially critical to establish measurement equivalence, or invariance, across the developmental periods. Similarly, when data from more than one study are combined into a single analysis, it is again important to assess measurement equivalence across the data sources. Yet, how to incorporate nonequivalence when it is discovered is not well described for applied researchers. Here, we present an item response theory approach that can be used to create scale scores from measures while explicitly accounting for nonequivalence. We demonstrate these methods in the context of a latent curve analysis in which data from two separate studies are combined to estimate a single longitudinal model spanning several developmental periods. 相似文献
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Sensitivity Analysis of the No-Omitted Confounder Assumption in Latent Growth Curve Mediation Models
Davood Tofighi Yu-Yu Hsiao Eric S. Kruger David P. MacKinnon M. Lee Van Horn Katie Witkiewitz 《Structural equation modeling》2019,26(1):94-109
Latent growth curve mediation models are increasingly used to assess mechanisms of behavior change. For latent growth mediation model, like any another mediation model, even with random treatment assignment, a critical but untestable assumption for valid and unbiased estimates of the indirect effects is that there should be no omitted variable that confounds indirect effects. One way to address this untestable assumption is to conduct sensitivity analysis to assess whether the inference about an indirect effect would change under varying degrees of confounding bias. We developed a sensitivity analysis technique for a latent growth curve mediation model. We compute the biasing effect of confounding on point and confidence interval estimates of the indirect effects in a structural equation modeling framework. We illustrate sensitivity plots to visualize the effects of confounding on each indirect effect and present an empirical example to illustrate the application of the sensitivity analysis. 相似文献
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Latent growth curve modeling employed data from a longitudinal study of 451 sibling families to examine parents, siblings, and family economics as factors in individual differences in the developmental course of interpersonal aggression during adolescence. Findings suggest that individual change in interpersonal aggression during adolescence can be predicted by the gender and aggression of one's sibling; predictions varied by the gender composition of the sibling dyad. Rates of parental hostility predicted levels of interpersonal aggression for both older (mean age = 12 years) and younger siblings (mean age = 15), and growth in aggression for younger siblings. Family economic pressure predicted interpersonal aggression of both siblings indirectly through parental hostility. Implications for future research and preventive interventions are discussed. 相似文献
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This article proposes a comprehensive approach based on structural equation modeling for assessing the amount of trait-level change derived from faking-motivating situations. The model is intended for a mixed 2-wave 2-group design, and assesses change at both the group and the individual level. Theoretically the model adopts an integrative approach that relates the 2 main current conceptualizations of faking, and models the amount of trait change as an individual-differences variable. The model and procedures are used in an empirical study based on 512 participants. Some of the results are interesting and warrant further research. Overall, the methodology that is proposed provides new resources for the theoretical and applied assessment of faking. In particular, it provides the practitioner with new tools for clearly assessing faking at the individual level. 相似文献
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This article compares two statistical approaches for modeling growth across time. The two statistical approaches are the multilevel model (MLM) and latent curve analysis (LCA), which have been proposed to depict change or growth adequately. These two approaches were compared in terms of the estimation of growth profiles represented by the parameters of initial status and the rate of growth. A longitudinal data set obtained from a school‐based substance‐use prevention trial for adolescents was used to illustrate the similarities and differences between the two approaches. The results indicated that the two approaches yielded very compatible results. The parameter estimates associated with regression weights are the same, whereas those associated with variances and covariances are similar. The MLM approach is easier for model specification and is more efficient computationally in yielding results. The LCA approach, however, has the advantage of providing model evaluation, that is, an overall test of goodness of fit, and is more flexible in modeling and hypothesis testing as demonstrated in this study. 相似文献
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Jacolyn Weller 《Teacher Development》2019,23(1):139-154
A central part of teacher education is critical reflection. To engage with the new – embrace change – is inherently difficult. The solution is teacher control of change. Those who embrace change, or not, are identified in their language. Pronoun analysis situates a teacher and determines areas of discomfort for change. Particular personal pronouns are evident when one is connected to, or distanced from, an artefact. This provides an avenue to individualise and pinpoint professional development (PD) requirements. Compared to traditional PD, this is efficient as it targets areas of discomfort for professional learning. Ideally, a teacher experiments with the new, indicates confidence and presents expertise to enable transmission into teaching. In this article, I illustrate how pronoun analysis was applied through interview data where science teachers were engaged in a discourse of Information Communication Technology integration. From this prior research data, a case is presented for individualised language analysis to direct PD. When a teacher is the active agent who self-analyses his or her own discomfort, an ownership pathway for directed proactive learning is created that goes beyond critical reflection into the new domain of critical analysis. 相似文献
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复杂适应系统理论是Holland于1994年正式提出的新一代系统理论,迄今已在经济、生物、哲学以及社会科学等领域得到成功应用.同样,该理论也为学者研究语言提供了新的理论框架.本文就是在这一背景下尝试探讨其对第二语言习得研究中的个体差异研究、写作研究以及研究方法的启示.个体差异是语言、主体和环境互动的产物,是动态化和过程... 相似文献
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Mike W.-L. Cheung 《Structural equation modeling》2013,20(1):157-167
Structural equation modeling (SEM) is now a generic modeling framework for many multivariate techniques applied in the social and behavioral sciences. Many statistical models can be considered either as special cases of SEM or as part of the latent variable modeling framework. One popular extension is the use of SEM to conduct linear mixed-effects modeling (LMM) such as cross-sectional multilevel modeling and latent growth modeling. It is well known that LMM can be formulated as structural equation models. However, one main difference between the implementations in SEM and LMM is that maximum likelihood (ML) estimation is usually used in SEM, whereas restricted (or residual) maximum likelihood (REML) estimation is the default method in most LMM packages. This article shows how REML estimation can be implemented in SEM. Two empirical examples on latent growth model and meta-analysis are used to illustrate the procedures implemented in OpenMx. Issues related to implementing REML in SEM are discussed. 相似文献
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Application of Latent Growth Curve Analysis With Categorical Responses in Social Behavioral Research
Tae Kyoung Lee Kandauda Wickrama Catherine W. O’Neal 《Structural equation modeling》2018,25(2):294-306
Latent growth modeling allows social behavioral researchers to investigate within-person change and between-person differences in within-person change. Typically, conventional latent growth curve models are applied to continuous variables, where the residuals are assumed to be normally distributed, whereas categorical variables (i.e., binary and ordinal variables), which do not hold to normal distribution assumptions, have rarely been used. This article describes the latent growth curve model with categorical variables, and illustrates applications using Mplus software that are applicable to social behavioral research. The illustrations use marital instability data from the Iowa Youth and Family Project. We close with recommendations for the specification and parameterization of growth models that use both logit and probit link functions. 相似文献
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Four methods of identifying change in the context of a multiple component reading intervention for struggling middle school readers 总被引：1，自引：0，他引：1
Jan C. Frijters Maureen W. Lovett Rose A. Sevcik Robin D. Morris 《Reading and writing》2013,26(4):539-563
The results from controlled intervention research have indicated that effective reading interventions exist for children with reading difficulties. Effect sizes for older struggling readers, however, typically have not matched the large effects demonstrated with younger children. Standardized effect sizes for intervention/control comparisons obscure important individual differences within intervention and control groups—differences potentially relevant to the who and why of intervention success. The present study reports the outcomes of PHAST Reading, a research-based multiple component reading intervention. Participants were 270 Grade 6, 7, and 8 students reading significantly below age-level expectations, who participated in a year-long intensive small-group intervention. Four methods were applied to characterize individual change: (a) normalization relative to age-appropriate standards; (b) statistically-reliable pre–post change using the Jacobson–Truax index; (c) individually-estimated growth rates using hierarchical linear modeling; and (d) change to a fixed criterion across multiple measures. Each method was evaluated for its ability to identify intervention outcomes, replicate traditional group-based effect size metrics, and characterize individual differences across participants depending on whether change was demonstrated. Each method replicated traditional group-based effect sizes, with advantages in consistency and predictive power for the reliable change index and growth curve approaches. 相似文献
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A Second-Order Conditionally Linear Mixed Effects Model With Observed and Latent Variable Covariates
A conditionally linear mixed effects model is an appropriate framework for investigating nonlinear change in a continuous latent variable that is repeatedly measured over time. The efficacy of the model is that it allows parameters that enter the specified nonlinear time-response function to be stochastic, whereas those parameters that enter in a nonlinear manner are common to all subjects. In this article we describe how a variant of the Michaelis-Menten (M-M) function can be fit within this modeling framework using Mplus 6.0. We demonstrate how observed and latent covariates can be incorporated to help explain individual differences in growth characteristics. Features of the model including an explication of key analytic decision points are illustrated using longitudinal reading data. To aid in making this class of models accessible, annotated Mplus code is provided. 相似文献
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Donald L. Compton 《Annals of dyslexia》2000,50(1):53-84
The purpose of this study was to identify important subject characteristics that predicted individual differences in responsiveness
to word reading instruction in normally achieving and at-risk first grade children. This was accomplished by modeling individual
word and nonword reading growth, and the correlates of change in these skills, in first grade students during two different
phases of the school year. In the first phase of the study (October–January), word and nonword reading skill was modeled in
normally achieving and at-risk children. Results of growth modeling indicated significant group differences in word and nonword
reading growth parameters. A combination of phonemic awareness skill, advanced graphophoneme knowledge, and initial word/nonword
reading skill predicted word and nonword reading growth in the control group, whereas, a combination of rapid naming speed,
letter sound knowledge, and phonemic awareness skill predicted word and nonword reading growth in the at-risk group. In the
second phase of the study (January–April), a subgroup of the at-risk subjects who exhibited limited growth in word reading
skills during the first phase of the study was enrolled in 12 weeks of small group reading intervention designed to improve
reading skills. Results of growth modeling indicated significant increases in word and nonword reading growth rates in this
group during the intervention phase. Only rapid naming speed uniquely predicted word and nonword reading growth in the group
of subjects receiving intervention. 相似文献
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Despite the widespread popularity of growth curve analysis, few studies have investigated robust growth curve models. In this article, the t distribution is applied to model heavy-tailed data and contaminated normal data with outliers for growth curve analysis. The derived robust growth curve models are estimated through Bayesian methods utilizing data augmentation and Gibbs sampling algorithms. The analysis of mathematical development data shows that the robust latent basis growth curve model better describes the mathematical growth trajectory than the corresponding normal growth curve model and can reveal the individual differences in mathematical development. Simulation studies further confirm that the robust growth curve models significantly outperform the normal growth curve models for both heavy-tailed t data and normal data with outliers but lose only slight efficiency for normal data. It appears convincing to replace the normal distribution with the t distribution for growth curve analysis. Three information criteria are evaluated for model selection. Online software is also provided for conducting robust analysis discussed in this study. 相似文献