Publication Date
In 2025 | 0 |
Since 2024 | 0 |
Since 2021 (last 5 years) | 1 |
Since 2016 (last 10 years) | 6 |
Descriptor
Bayesian Statistics | 6 |
Longitudinal Studies | 5 |
Computation | 2 |
Data Analysis | 2 |
Maximum Likelihood Statistics | 2 |
Models | 2 |
Simulation | 2 |
Statistical Analysis | 2 |
Accuracy | 1 |
Adolescents | 1 |
Adults | 1 |
More ▼ |
Source
International Journal of… | 6 |
Author
Davison, Mark L. | 1 |
De Jesús, Sue A. Rodríguez | 1 |
Depaoli, Sarah | 1 |
Hecht, Martin | 1 |
Huh, David | 1 |
Killoren, Sarah E. | 1 |
Kim, Su-Young | 1 |
Kohli, Nidhi | 1 |
Meissner, Tobias W. | 1 |
Mun, Eun-Young | 1 |
Nordt, Marisa | 1 |
More ▼ |
Publication Type
Journal Articles | 6 |
Reports - Research | 5 |
Reports - Descriptive | 1 |
Education Level
Elementary Education | 1 |
Grade 7 | 1 |
Higher Education | 1 |
Junior High Schools | 1 |
Middle Schools | 1 |
Postsecondary Education | 1 |
Secondary Education | 1 |
Audience
Location
Arizona (Phoenix) | 1 |
Germany | 1 |
Laws, Policies, & Programs
Assessments and Surveys
Childrens Report of Parental… | 1 |
What Works Clearinghouse Rating
Hecht, Martin; Voelkle, Manuel C. – International Journal of Behavioral Development, 2021
The analysis of cross-lagged relationships is a popular approach in prevention research to explore the dynamics between constructs over time. However, a limitation of commonly used cross-lagged models is the requirement of equally spaced measurement occasions that prevents the usage of flexible longitudinal designs and complicates cross-study…
Descriptors: Models, Longitudinal Studies, Prevention, Time
Kim, Su-Young; Huh, David; Zhou, Zhengyang; Mun, Eun-Young – International Journal of Behavioral Development, 2020
Latent growth models (LGMs) are an application of structural equation modeling and frequently used in developmental and clinical research to analyze change over time in longitudinal outcomes. Maximum likelihood (ML), the most common approach for estimating LGMs, can fail to converge or may produce biased estimates in complex LGMs especially in…
Descriptors: Bayesian Statistics, Maximum Likelihood Statistics, Longitudinal Studies, Models
Winter, Sonja D.; Depaoli, Sarah – International Journal of Behavioral Development, 2020
This article illustrates the Bayesian approximate measurement invariance (MI) approach in Mplus with longitudinal data and small sample size. Approximate MI incorporates zero-mean small variance prior distributions on the differences between parameter estimates over time. Contrary to traditional invariance testing methods, where exact invariance…
Descriptors: Bayesian Statistics, Measurement, Data Analysis, Sample Size
Kohli, Nidhi; Peralta, Yadira; Zopluoglu, Cengiz; Davison, Mark L. – International Journal of Behavioral Development, 2018
Piecewise mixed-effects models are useful for analyzing longitudinal educational and psychological data sets to model segmented change over time. These models offer an attractive alternative to commonly used quadratic and higher-order polynomial models because the coefficients obtained from fitting the model have meaningful substantive…
Descriptors: Hierarchical Linear Modeling, Longitudinal Studies, Maximum Likelihood Statistics, Bayesian Statistics
Meissner, Tobias W.; Prüfer, Helen; Nordt, Marisa; Semmelmann, Kilian; Weigelt, Sarah – International Journal of Behavioral Development, 2018
We investigated the ability to detect a face among other visual objects in a complex visual array in 3-, 4-, and 5-year-old children, as well as in adults. To this end, we used a visual search paradigm implemented on a touch-tablet device. Subjects (N = 100) saw up to eighty 3 × 3 visual search arrays and had to find and tap upon a target--a face…
Descriptors: Preschool Children, Human Body, Cognitive Development, Adults
Killoren, Sarah E.; De Jesús, Sue A. Rodríguez; Updegraff, Kimberly A.; Wheeler, Lorey A. – International Journal of Behavioral Development, 2017
We examined profiles of sibling relationship qualities in 246 Mexican-origin families living in the United States using latent profile analyses. Three profiles were identified: "Positive," "Negative," and "Affect-Intense." Links between profiles and youths' familism values and adjustment were assessed using…
Descriptors: Sibling Relationship, Adolescents, Family Needs, Siblings