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University of Nebraska - Lincoln
Developmental Cognitive Neuroscience Laboratory: Faculty and Staff Publications
- Keyword
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- Academic achievement (1)
- Covariance structure (1)
- Fuzzy clustering (1)
- Growth mixture modeling (1)
- Growth pattern recognition (1)
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- Hierarchical multivariate linear models (1)
- Intermittent missing (1)
- Latent class identification (1)
- Longitudinal study (1)
- Low birth weight (1)
- Mathematics learning disabilities (1)
- Neuropsychological impairment (1)
- Nonmissing at random (1)
- Parallel mixture model (1)
- Power analysis (1)
- Prematurity (1)
- Preschool children (1)
- Processing speed (1)
- Traditional repeated measures (1)
- Very low birth weight (1)
Articles 1 - 6 of 6
Full-Text Articles in Medicine and Health Sciences
Mathematics Deficiencies In Children With Very Low Birth Weight Or Very Preterm Birth, H. Gerry Taylor, Kimberly A. Espy, Peter J. Anderson
Mathematics Deficiencies In Children With Very Low Birth Weight Or Very Preterm Birth, H. Gerry Taylor, Kimberly A. Espy, Peter J. Anderson
Developmental Cognitive Neuroscience Laboratory: Faculty and Staff Publications
Abstract Children with very low birth weight (VLBW, < 1500 g) or very pre-term birth (VPTB, < 32 weeks gestational age or GA) have more mathematics disabilities or deficiencies (MD) and higher rates of mathematics learning disabilities (MLD) than normal birth weight term-born children (NBW, > 2500 g and > 36 weeks GA). MD are found even in children without global disorders in cognition or neurosensory status and when IQ is controlled, and they are associated with other learning problems and weaknesses in perceptual motor abilities and executive function. Factors related to poorer mathematics outcomes include lower birth weight and GA, neonatal complications, and possible abnormalities in brain structure. While little is known about the nature of MD in these children, studies of MLD in other neurodevelopmental disorders and in children with learning disabilities provide useful models for further …
Age-Related Differences In Reaction Time Task Performance In Young Children, Sergey Kiselev, Kimberly A. Espy, Tiffany Sheffield
Age-Related Differences In Reaction Time Task Performance In Young Children, Sergey Kiselev, Kimberly A. Espy, Tiffany Sheffield
Developmental Cognitive Neuroscience Laboratory: Faculty and Staff Publications
Performance of reaction time (RT) tasks was investigated in young children and adults to test the hypothesis that age-related differences in processing speed supersede a “global” mechanism and are a function of specific differences in task demands and processing requirements. The sample consisted of 54 4-year-olds, 53 5-year-olds, 59 6-year-olds, and 35 adults from Russia. Using the regression approach pioneered by Brinley and the transformation method proposed by Madden and colleagues and Ridderinkhoff and van der Molen, age-related differences in processing speed differed among RT tasks with varying demands. In particular, RTs differed between children and adults on tasks that …
Viewing Preschool Disruptive Behavior Disorders And Attention-Deficit/Hyperactivity Disorder Through A Developmental Lens: What We Know And What We Need To Know, Anil Chacko, Lauren Wakschlag, Carri Hill, Barbara Danis, Kimberly A. Espy
Viewing Preschool Disruptive Behavior Disorders And Attention-Deficit/Hyperactivity Disorder Through A Developmental Lens: What We Know And What We Need To Know, Anil Chacko, Lauren Wakschlag, Carri Hill, Barbara Danis, Kimberly A. Espy
Developmental Cognitive Neuroscience Laboratory: Faculty and Staff Publications
Although DSM-defined DBDs and ADHD manifest during early childhood in meaning¬ful ways, the emphasis of extending the DBD and ADHD nosology, which is based on studies of older youth, to younger children potentially limits the utility of these symptoms. Given that it is clear that DBDs and ADHD often emerge during early childhood and that early intervention is most efficacious, developing a more refined understanding of the clinical phenomenology of behavior disorders in early childhood is a critical next step. We contend that an approach that emphasizes the developmental specification of symptoms has the potential to address several long-standing issues …
Growth Mixture Modeling Of Academic Achievement In Children Of Varying Birth Weight Risk, Kimberly A. Espy, Julia Hua Fang, David Charak, Nori Minich, H. Gerry Taylor
Growth Mixture Modeling Of Academic Achievement In Children Of Varying Birth Weight Risk, Kimberly A. Espy, Julia Hua Fang, David Charak, Nori Minich, H. Gerry Taylor
Developmental Cognitive Neuroscience Laboratory: Faculty and Staff Publications
The extremes of birth weight and preterm birth are known to result in a host of adverse outcomes, yet studies to date largely have used cross-sectional designs and variable-centered methods to understand long-term sequelae. Growth mixture modeling (GMM) that utilizes an integrated person- and variable-centered approach was applied to identify latent classes of achievement from a cohort of school-age children born at varying birth weights. GMM analyses revealed 2 latent achievement classes for calculation, problem-solving, and decoding abilities. The classes differed substantively and persistently in proficiency and in growth trajectories. Birth weight was a robust predictor of class membership for …
Power Of Models In Longitudinal Study: Findings From A Full- Crossed Simulation Design, Hua Fang, Gordon P. Brooks, Maria L. Rizzo, Kimberly A. Espy, Robert S. Barcikowski
Power Of Models In Longitudinal Study: Findings From A Full- Crossed Simulation Design, Hua Fang, Gordon P. Brooks, Maria L. Rizzo, Kimberly A. Espy, Robert S. Barcikowski
Developmental Cognitive Neuroscience Laboratory: Faculty and Staff Publications
Because the power properties of traditional repeated measures and hierarchical multivariate linear models have not been clearly determined in the balanced design for longitudinal studies in the literature, the authors present a power comparison study of traditional repeated measures and hierarchical multivariate linear models under 3 variance-covariance structures. The results from a full-crossed simulation design suggest that traditional repeated measures have significantly higher power than do hierarchical multivariate linear models for main effects, but they have significantly lower power for interaction effects in most situations. Significant power differences are also exhibited when power is compared across different covariance structures.
Pattern Recognition Of Longitudinal Trial Data With Nonignorable Missingness: An Empirical Case Study, Julia Hua Fang, Kimberly A. Espy, Maria L. Rizzo, Christian Stopp, Sandra A. Wiebe, Walter W. Stroup
Pattern Recognition Of Longitudinal Trial Data With Nonignorable Missingness: An Empirical Case Study, Julia Hua Fang, Kimberly A. Espy, Maria L. Rizzo, Christian Stopp, Sandra A. Wiebe, Walter W. Stroup
Developmental Cognitive Neuroscience Laboratory: Faculty and Staff Publications
Methods for identifying meaningful growth patterns of longitudinal trial data with both nonignorable intermittent and drop-out missingness are rare. In this study, a combined approach with statistical and data mining techniques is utilized to address the nonignorable missing data issue in growth pattern recognition. First, a parallel mixture model is proposed to model the nonignorable missing information from a real-world patient-oriented study and concurrently to estimate the growth trajectories of participants. Then, based on individual growth parameter estimates and their auxiliary feature attributes, a fuzzy clustering method is incorporated to identify the growth patterns. This case study demonstrates that the …