scholarly journals Dynamical Properties and Conceptual Interpretation of Latent Change Score Models

2021 ◽  
Vol 12 ◽  
Author(s):  
Pablo F. Cáncer ◽  
Eduardo Estrada ◽  
Mar J. F. Ollero ◽  
Emilio Ferrer
Keyword(s):  
Longitudinal Research ◽  
Change Score ◽  
Model Parameters ◽  
Shiny App ◽  
Dual Interpretation ◽  
R Packages ◽  
Latent Change Score ◽  
Parameter Values ◽  
Long Term Behavior

Latent Change Score models (LCS) are a popular tool for the study of dynamics in longitudinal research. They represent processes in which the short-term dynamics have direct and indirect consequences on the long-term behavior of the system. However, this dual interpretation of the model parameters is usually overlooked in the literature, and researchers often find it difficult to see the connection between parameters and specific patterns of change. The goal of this paper is to provide a comprehensive examination of the meaning and interpretation of the parameters in LCS models. Importantly, we focus on their relation to the shape of the trajectories and explain how different specifications of the LCS model involve particular assumptions about the mechanisms of change. On a supplementary website, we present an interactive Shiny App that allows users to explore different sets of parameter values and examine their effects on the predicted trajectories. We also include fully explained code to estimate some of the most relevant specifications of the LCS model with the R-packages lavaan and OpenMx.

Application of A Monte Carlo Approach to Surface Complexation Modelling

2004 ◽  
Vol 824 ◽  
Author(s):  
M.M. Askarieh ◽  
T.G. Heath ◽  
W.M. Tearle
Keyword(s):  
Monte Carlo ◽  
Model Parameters ◽  
Surface Complexes ◽  
Monte Carlo Approach ◽  
Ion Sorption ◽  
Wide Range ◽  
Complex Models ◽  
Chemical Conditions ◽  
Parameter Values

AbstractA Monte Carlo-based approach has been adopted for development of a chemical thermodynamic model to describe the goethite surface in contact with sodium nitrate solutions. The technique involves the calculation of the goethite surface properties for the chemical conditions corresponding to each experimental data point. The representation of the surface was based on a set of model parameters, each of which was either fixed or was randomly sampled from a specified range of values. Thousands of such model representations were generated for different selected sets of parameter values with the use of the standard geochemical speciation computer program, HARPHRQ. The method allowed many combinations of parameter values to be sampled that might not be achieved with a simple least-squares fitting approach. It also allowed the dependence of the quality of fit on each parameter to be analysed. The Monte Carlo approach is most appropriate in the development of complex models involving the fitting of several datasets with several fitting parameters.Introduction of selenate surface complexes allowed the model to be extended to represent selenate ion sorption, selenium being an important radioelement in evaluation of the long-term safety of ILW disposal. The sorption model gave good agreement with a wide range of experimental sorption datasets for selenate.

Long-term behavior of R7T7-type nuclear glass: Current state of knowledge and outlook

2004 ◽  
Vol 824 ◽  
Author(s):  
S. Gin ◽  
N. Godon ◽  
I. Ribet ◽  
P. Jollivet ◽  
Y. Minet ◽  
...  
Keyword(s):  
Current Knowledge ◽  
Influential Factors ◽  
Future Research ◽  
Operational Model ◽  
Geological Repository ◽  
Glass Current ◽  
Interim Storage ◽  
Parameter Values ◽  
Long Term Behavior

AbstractThis article reviews current knowledge of the long-term behavior of R7T7-type glass during the thermal phase and in geological repository conditions (aqueous alteration). In interim storage R7T7 glass can be considered to conserve its integrity over time. In geological repository conditions, the mechanisms of glass alteration by water have been identified and parameter values have been assigned to the reaction kinetics for wide variations of the influential factors (temperature, pH, flow rate, S/V ratio, etc.). CEA has developed an operational model to obtain robust and reasonably conservative predictions of the glass quantities altered after disposal. Examples of applications of the operational model are discussed, future research topics are also proposed to consolidate this approach.

scholarly journals Developmental cognitive neuroscience using Latent Change Score models: A tutorial and applications

2017 ◽  
Author(s):  
Rogier A. Kievit ◽  
Andreas M. Brandmaier ◽  
Gabriel Ziegler ◽  
Anne-Laura van Harmelen ◽  
Susanne M. M. de Mooij ◽  
...  
Keyword(s):  
Change Score ◽  
Model Parameters ◽  
List Type ◽  
Statistical Tool ◽  
Cross Sectional ◽  
High Intensity Training ◽  
Complex Processes ◽  
Statistical Framework ◽  
Developmental Neuroscience ◽  
Latent Change Score

AbstractAssessing and analysing individual differences in change over time is of central scientific importance to developmental neuroscience. However, the literature is based largely on cross-sectional comparisons, which reflect a variety of influences and cannot directly represent change. We advocate using latent change score (LCS) models in longitudinal samples as a statistical framework to tease apart the complex processes underlying lifespan development in brain and behaviour using longitudinal data. LCS models provide a flexible framework that naturally accommodates key developmental questions as model parameters and can even be used, with some limitations, in cases with only two measurement occasions. We illustrate the use of LCS models with two empirical examples. In a lifespan cognitive training study (COGITO, N=204 (N=32 imaging) on two waves) we observe correlated change in brain and behaviour in the context of a high-intensity training intervention. In an adolescent development cohort (NSPN, N=176, two waves) we find greater variability in cortical thinning in males than in females. To facilitate the adoption of LCS by the developmental community, we provide analysis code that can be adapted by other researchers and basic primers in two freely available SEM software packages (lavaan and Ωnyx).HighlightsWe describe Latent change score modelling as a flexible statistical toolKey developmental questions can be readily formalized using LCS modelsWe provide accessible open source code and software examples to fit LCS modelsWhite matter structural change is negatively correlated with processing speed gainsFrontal lobe thinning in adolescence is more variable in males than females

Correlated personality change across time and age

2021 ◽  
pp. 089020702110140
Author(s):  
Gabriel Olaru ◽  
Mathias Allemand
Keyword(s):  
Structural Equation ◽  
Rank Order ◽  
Personality Development ◽  
The United States ◽  
Change Score ◽  
Personality Change ◽  
Equation Modeling ◽  
Model Parameters ◽  
Cross Sectional ◽  
Adult Lifespan

The goal of this study was to examine differential and correlated change in personality across the adult lifespan. Studying differential and correlated change can help understand whether intraindividual trait change trajectories deviate from the norm and how these trajectories are coupled with each other. We used data from two large longitudinal panel studies from the United States that covered a total age range of 20 to 95 years on the first measurement occasion. We used correlated factor models and bivariate latent change score models to examine the rank-order stability and correlations between change across three measurement waves covering 18 years ( N = 3250) and four measurement waves covering 12 years ( N = 4145). We examined the moderation effects of continuous age on these model parameters using local structural equation modeling. The results suggest that the test–retest correlations decrease with increasing time between measurements but are unaffected by participants’ age. We found that change processes in Extraversion, Openness, Agreeableness, and Conscientiousness were strongly related, particularly in late adulthood. Correlated change patterns were highly stable across time intervals and similar to the initial cross-sectional Big Five correlations. We discuss potential mechanisms and implications for personality development research.

scholarly journals Measuring the long-term effects of informal science education experiences: challenges and potential solutions

2021 ◽  
Vol 3 (1) ◽  
Author(s):  
Nancy L. Staus ◽  
John H. Falk ◽  
Aaron Price ◽  
Robert H. Tai ◽  
Lynn D. Dierking
Keyword(s):  
Science Learning ◽  
Longitudinal Research ◽  
Informal Science Education ◽  
Informal Science ◽  
Long Term Effects ◽  
Science Center ◽  
Informal Science Learning ◽  
Learner Outcomes ◽  
Key Issues

AbstractDespite the fact that most science learning takes place outside of school, little is known about how engagement in informal science learning (ISL) experiences affects learners’ knowledge, skill development, interest, or identities over long periods of time. Although substantial ISL research has documented short-term outcomes such as the learning that takes place during a science center visit, research suggests that the genuine benefits of informal experiences are long-term transformations in learners as they pursue a “cascade” of experiences subsequent to the initial educational event. However, a number of major methodological challenges have limited longitudinal research projects investigating the long-term effects of ISL experiences. In this paper we identify and address four key issues surrounding the critical but challenging area of how to study and measure the long-term effects or impacts of ISL experiences: attribution, attrition, data collection, and analytic approaches. Our objective is to provide guidance to ISL researchers wishing to engage in long-term investigations of learner outcomes and to begin a dialogue about how best to address the numerous challenges involved in this work.

scholarly journals Wood creep data collection and unbiased parameter identification of compliance functions

Holzforschung ◽  
2020 ◽  
Vol 74 (11) ◽  
pp. 1011-1020
Author(s):  
Danyang Tong ◽  
Susan Alexis Brown ◽  
David Corr ◽  
Gianluca Cusatis
Keyword(s):  
Parameter Identification ◽  
Prediction Models ◽  
Tall Buildings ◽  
Building Design ◽  
Parameter Distribution ◽  
Experimental Conditions ◽  
Global Emission ◽  
Wood Construction ◽  
Parameter Values

AbstractRising global emission have led to a renewed popularity of timber in building design, including timber-concrete tall buildings up to 18 stories. In spite of this surge in wood construction, there remains a gap in understanding of long-term structural behavior, particularly wood creep. Unlike concrete, code prescriptions for wood design are lacking in robust estimates for structural shortening. Models for wood creep have become increasingly necessary due to the potential for unforeseen shortening, especially with respect to differential shortening. These effects can have serious impacts as timber building heights continue to grow. This study lays the groundwork for wood compliance prediction models for use in timber design. A thorough review of wood creep studies was conducted and viable experimental results were compiled into a database. Studies were chosen based on correlation of experimental conditions with a realistic building environment. An unbiased parameter identification method, originally applied to concrete prediction models, was used to fit multiple compliance functions to each data curve. Based on individual curve fittings, statistical analysis was performed to determine the best fit function and average parameter values for the collective database. A power law trend in wood creep, with lognormal parameter distribution, was confirmed by the results.

scholarly journals Abnormal Liver Function Tests and Long-Term Outcomes in Patients Discharged after Acute Heart Failure

2021 ◽  
Vol 10 (8) ◽  
pp. 1730
Author(s):  
Hiroshi Miyama ◽  
Yasuyuki Shiraishi ◽  
Shun Kohsaka ◽  
Ayumi Goda ◽  
Yosuke Nishihata ◽  
...  
Keyword(s):  
Heart Failure ◽  
Liver Function ◽  
Liver Function Tests ◽  
Abnormal Liver Function ◽  
Adverse Outcomes ◽  
Long Term Outcomes ◽  
Function Tests ◽  
Parameter Values

Abnormal liver function tests (LFTs) are known to be associated with impaired clinical outcomes in heart failure (HF) patients. However, this implication varies with each single LFT panel. We aim to evaluate the long-term outcomes of acute HF (AHF) patients by assessing multiple LFT panels in combination. From a prospective multicenter registry in Japan, 1158 AHF patients who were successfully discharged were analyzed (mean age, 73.9 ± 13.5 years; men, 58%). LFTs (i.e., total bilirubin, aspartate aminotransferase or alanine aminotransferase, and alkaline phosphatase) at discharge were assessed; borderline and abnormal LFTs were defined as 1 and ≥2 parameter values above the normal range, respectively. The primary endpoint was composite of all-cause death or HF readmission. At the time of discharge, 28.7% and 8.6% of patients showed borderline and abnormal LFTs, respectively. There were 196 (16.9%) deaths and 298 (25.7%) HF readmissions during a median 12.4-month follow-up period. The abnormal LFTs group had a significantly higher risk of experiencing the composite outcome (adjusted hazard ratio: 1.51, 95% confidence interval: 1.08–2.12, p = 0.017), whereas the borderline LFTs group was not associated with higher risk of adverse events when referenced to the normal LFTs group. Among AHF patients, the combined elevation of ≥2 LFT panels at discharge was associated with long-term adverse outcomes.

scholarly journals Assimilation of Dynamic Combined Finite Discrete Element Methods Using the Ensemble Kalman Filter

2021 ◽  
Vol 11 (7) ◽  
pp. 2898
Author(s):  
Humberto C. Godinez ◽  
Esteban Rougier
Keyword(s):  
Kalman Filter ◽  
Ensemble Kalman Filter ◽  
Failure Modes ◽  
Split Hopkinson Pressure Bar ◽  
Peak Stress ◽  
Discrete Element ◽  
Material Behavior ◽  
Model Parameters ◽  
Hopkinson Pressure Bar ◽  
Parameter Values

Simulation of fracture initiation, propagation, and arrest is a problem of interest for many applications in the scientific community. There are a number of numerical methods used for this purpose, and among the most widely accepted is the combined finite-discrete element method (FDEM). To model fracture with FDEM, material behavior is described by specifying a combination of elastic properties, strengths (in the normal and tangential directions), and energy dissipated in failure modes I and II, which are modeled by incorporating a parameterized softening curve defining a post-peak stress-displacement relationship unique to each material. In this work, we implement a data assimilation method to estimate key model parameter values with the objective of improving the calibration processes for FDEM fracture simulations. Specifically, we implement the ensemble Kalman filter assimilation method to the Hybrid Optimization Software Suite (HOSS), a FDEM-based code which was developed for the simulation of fracture and fragmentation behavior. We present a set of assimilation experiments to match the numerical results obtained for a Split Hopkinson Pressure Bar (SHPB) model with experimental observations for granite. We achieved this by calibrating a subset of model parameters. The results show a steady convergence of the assimilated parameter values towards observed time/stress curves from the SHPB observations. In particular, both tensile and shear strengths seem to be converging faster than the other parameters considered.

scholarly journals Agglomeration economies, congestion diseconomies, and fertility dynamics in a two-region economy

2021 ◽  
Author(s):  
Madoka Muroishi ◽  
Akira Yakita
Keyword(s):  
Population Size ◽  
Stability Condition ◽  
Fertility Rate ◽  
Model Parameters ◽  
Initial Population ◽  
Interregional Migration ◽  
Stable Path ◽  
Regional Population ◽  
Initial Population Size

AbstractUsing a small, open, two-region economy model populated by two-period-lived overlapping generations, we analyze long-term agglomeration economy and congestion diseconomy effects of young worker concentration on migration and the overall fertility rate. When the migration-stability condition is satisfied, the distribution of young workers between regions is obtainable in each period for a predetermined population size. Results show that migration stability does not guarantee dynamic stability of the economy. The stationary population size stability depends on the model parameters and the initial population size. On a stable trajectory converging to the stationary equilibrium, the overall fertility rate might change non-monotonically with the population size of the economy because of interregional migration. In each period, interregional migration mitigates regional population changes caused by fertility differences on the stable path. Results show that the inter-regional migration-stability condition does not guarantee stability of the population dynamics of the economy.

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