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Showing 1 to 15 of 22 results Save | Export
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Xiaohui Luo; Yueqin Hu – Structural Equation Modeling: A Multidisciplinary Journal, 2024
Intensive longitudinal data has been widely used to examine reciprocal or causal relations between variables. However, these variables may not be temporally aligned. This study examined the consequences and solutions of the problem of temporal misalignment in intensive longitudinal data based on dynamic structural equation models. First the impact…
Descriptors: Structural Equation Models, Longitudinal Studies, Data Analysis, Causal Models
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Schochet, Peter Z. – Journal of Educational and Behavioral Statistics, 2022
This article develops new closed-form variance expressions for power analyses for commonly used difference-in-differences (DID) and comparative interrupted time series (CITS) panel data estimators. The main contribution is to incorporate variation in treatment timing into the analysis. The power formulas also account for other key design features…
Descriptors: Comparative Analysis, Statistical Analysis, Sample Size, Measurement Techniques
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Nazari, Sanaz; Leite, Walter L.; Huggins-Manley, A. Corinne – Journal of Experimental Education, 2023
The piecewise latent growth models (PWLGMs) can be used to study changes in the growth trajectory of an outcome due to an event or condition, such as exposure to an intervention. When there are multiple outcomes of interest, a researcher may choose to fit a series of PWLGMs or a single parallel-process PWLGM. A comparison of these models is…
Descriptors: Growth Models, Statistical Analysis, Intervention, Comparative Analysis
Xu, Jie – ProQuest LLC, 2019
Research has shown that cross-sectional mediation analysis cannot accurately reflect a true longitudinal mediated effect. To investigate longitudinal mediated effects, different longitudinal mediation models have been proposed and these models focus on different research questions related to longitudinal mediation. When fitting mediation models to…
Descriptors: Case Studies, Error of Measurement, Longitudinal Studies, Models
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Cao, Chunhua; Kim, Eun Sook; Chen, Yi-Hsin; Ferron, John; Stark, Stephen – Educational and Psychological Measurement, 2019
In multilevel multiple-indicator multiple-cause (MIMIC) models, covariates can interact at the within level, at the between level, or across levels. This study examines the performance of multilevel MIMIC models in estimating and detecting the interaction effect of two covariates through a simulation and provides an empirical demonstration of…
Descriptors: Hierarchical Linear Modeling, Structural Equation Models, Computation, Identification
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Temel, Gülhan Orekici; Erdogan, Semra; Selvi, Hüseyin; Kaya, Irem Ersöz – Educational Sciences: Theory and Practice, 2016
Studies based on longitudinal data focus on the change and development of the situation being investigated and allow for examining cases regarding education, individual development, cultural change, and socioeconomic improvement in time. However, as these studies require taking repeated measures in different time periods, they may include various…
Descriptors: Investigations, Sample Size, Longitudinal Studies, Interrater Reliability
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Long, Mark C. – Journal of Research on Educational Effectiveness, 2016
Using a "naïve" specification, this paper estimates the relationship between 36 high school characteristics and 24 student outcomes controlling for students' pre-high school characteristics. The goal of this exploration is not to generate casual estimates, but rather to: (a) compare the size of the relationships to determine which inputs…
Descriptors: Hypothesis Testing, Effect Size, High School Students, Student Characteristics
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Liu, Siwei; Rovine, Michael J.; Molenaar, Peter C. M. – Structural Equation Modeling: A Multidisciplinary Journal, 2012
This study investigated the performance of fit indexes in selecting a covariance structure for longitudinal data. Data were simulated to follow a compound symmetry, first-order autoregressive, first-order moving average, or random-coefficients covariance structure. We examined the ability of the likelihood ratio test (LRT), root mean square error…
Descriptors: Structural Equation Models, Goodness of Fit, Longitudinal Studies, Data Analysis
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Lucas, Richard E.; Donnellan, M. Brent – Social Indicators Research, 2012
Life satisfaction is often assessed using single-item measures. However, estimating the reliability of these measures can be difficult because internal consistency coefficients cannot be calculated. Existing approaches use longitudinal data to isolate occasion-specific variance from variance that is either completely stable or variance that…
Descriptors: Life Satisfaction, Measurement, Error of Measurement, Reliability
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Peugh, James; Fan, Xitao – Structural Equation Modeling: A Multidisciplinary Journal, 2012
Growth mixture modeling (GMM) has become a more popular statistical method for modeling population heterogeneity in longitudinal data, but the performance characteristics of GMM enumeration indexes in correctly identifying heterogeneous growth trajectories are largely unknown. Few empirical studies have addressed this issue. This study considered…
Descriptors: Structural Equation Models, Statistical Analysis, Longitudinal Studies, Evaluation Research
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Brown, Jane D. – Developmental Psychology, 2011
Steinberg and Monahan's (2011) reanalysis of the Teen Media longitudinal survey of adolescents does not meet prevailing standards for propensity score analysis and therefore does not undermine the original conclusions of the Brown, L'Engle, Pardun, Guo, Kenneavy, and Jackson (2006) analysis. The media do matter in the sexual socialization of…
Descriptors: Socialization, Adolescents, Scores, Sexuality
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Reichardt, Charles S. – Multivariate Behavioral Research, 2011
Maxwell, Cole, and Mitchell (2011) demonstrated that simple structural equation models, when used with cross-sectional data, generally produce biased estimates of meditated effects. I extend those results by showing how simple structural equation models can produce biased estimates of meditated effects when used even with longitudinal data. Even…
Descriptors: Structural Equation Models, Statistical Data, Longitudinal Studies, Error of Measurement
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Tourangeau, Karen; Nord, Christine; Lê, Thanh; Wallner-Allen, Kathleen; Vaden-Kiernan, Nancy; Blaker, Lisa; Najarian, Michelle – National Center for Education Statistics, 2018
This manual provides guidance and documentation for users of the longitudinal kindergarten-fourth grade (K-4) public-use data file of the Early Childhood Longitudinal Study, Kindergarten Class of 2010-11 (ECLS-K:2011), which includes the first release of the public version of the third-grade data. This manual mainly provides information specific…
Descriptors: Longitudinal Studies, Children, Surveys, Kindergarten
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Hertzog, Christopher; von Oertzen, Timo; Ghisletta, Paolo; Lindenberger, Ulman – Structural Equation Modeling: A Multidisciplinary Journal, 2008
We evaluated the statistical power of single-indicator latent growth curve models to detect individual differences in change (variances of latent slopes) as a function of sample size, number of longitudinal measurement occasions, and growth curve reliability. We recommend the 2 degree-of-freedom generalized test assessing loss of fit when both…
Descriptors: Sample Size, Error of Measurement, Individual Differences, Statistical Analysis
Maynard, Rebecca; Dong, Nianbo – Society for Research on Educational Effectiveness, 2009
This study empirically investigates the effectiveness of Distributed Leadership Teacher Training (DLT) program on improving student's academic achievement. In addition, it both tests the assumption that the year 1 impacts are stable across calendar years and examines the importance of properly accounting for the fact that the standard error of the…
Descriptors: Urban Schools, Middle School Students, Elementary School Students, Sample Size
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