scholarly journals Science Self-Concept – More Than the Sum of its Parts? A Comparison of Different Assessment and Modeling Approaches

2019 ◽  
Author(s):  
Ulrich Schroeders ◽  
Malte Jansen
Keyword(s):  
Structural Equation ◽  
Large Scale ◽  
Structural Equation Models ◽  
Factor Model ◽  
Self Concept ◽  
General Science ◽  
Theoretical Status ◽  
Subject Specific ◽  
Mean Structure ◽  
The Subject

Academic self-concept is understood as a multidimensional, hierarchical construct. Multidimensionality refers to the subject-specific differentiation of academic self-concepts, whereas hierarchy refers to the aggregation of more specific facets of self-concepts into more general ones. Previous research demonstrated that students distinguish between their self-concepts in biology, chemistry, and physics if taught as separate school subjects, as is done in Germany. However, large-scale international educational studies, such as PISA, often use a monolithic science self-concept measure. It is yet unclear whether an aggregate of subject-specific self-concepts is equivalent to a directly measured science self-concept. We assessed the subject-specific and and a general science self-concept of 1,232 German grade 10 students. A higher-order factor model and a bifactor model demonstrated a very high correlation between the “inferred” and the explicitly assessed general science self-concept. Despite the high empirical overlap, we argue for a more nuanced view of the science self-concept, because statistical unity is not to be confused with causal unity. Moreover, from a methodological perspective, we used multi-group confirmatory factor analysis to examine the mean structure and local weighted structural equation models to study measurement invariance across science ability. Implications for the theoretical status of self-concept as a hierarchical construct are discussed.

The Dimensionality of Reading Self-Concept: Examining Its Stability Using Local Structural Equation Models

Assessment ◽  
2022 ◽  
pp. 107319112110696
Author(s):  
Geetanjali Basarkod ◽  
Herbert W. Marsh ◽  
Baljinder K. Sahdra ◽  
Philip D. Parker ◽  
Jiesi Guo ◽  
...  
Keyword(s):  
Reading Achievement ◽  
Structural Equation ◽  
Large Scale ◽  
Structural Equation Models ◽  
Student Assessment ◽  
Cognitive Testing ◽  
Self Concept ◽  
International Student Assessment ◽  
High Competence ◽  
Achievement Levels

For results from large-scale surveys to inform policy and practice appropriately, all participants must interpret and respond to items similarly. While organizers of surveys assessing student outcomes often ensure this for achievement measures, doing so for psychological questionnaires is also critical. We demonstrate this by examining the dimensionality of reading self-concept—a crucial psychological construct for several outcomes—across reading achievement levels. We use Programme for International Student Assessment 2018 data ( N = 529,966) and local structural equation models (LSEMs) to do so. Results reveal that reading self-concept dimensions (assessed through reading competence and difficulty) vary across reading achievement levels. Students with low reading achievement show differentiated responses to the two item sets (high competence–high difficulty). In contrast, students with high reading achievement have reconciled responses (high competence–low difficulty). Our results highlight the value of LSEMs in examining factor structure generalizability of constructs in large-scale surveys and call for greater cognitive testing during item development.

scholarly journals The Structure of Academic Self-Concept When Facing Novel Learning Content: Multidimensionality, Hierarchy, and Change

2019 ◽  
Vol 15 (3) ◽  
pp. 491-508
Author(s):  
Julia Gorges ◽  
Jelena Hollmann
Keyword(s):  
Structural Change ◽  
Structural Equation ◽  
Structural Model ◽  
Structural Equation Models ◽  
Self Concept ◽  
Study Phase ◽  
Field Of Study ◽  
Study Program ◽  
Method Factor ◽  
Subject Specific

Academic self-concepts of ability are key factors in promoting education and learning throughout students’ school career. Yet we know little about their structure and structural change when students leave high school to face novel academic tasks. The present study investigated the structure and structural change of first-year students’ study-related self-concepts of ability. Data stems from a longitudinal study with two measurement points covering the initial study phase (t1: N = 341; age: M = 21.6; SD = 3.56; 57.5% female). Self-concepts were assessed regarding the participants’ study program and four of its subordinate subjects. Confirmatory factor analyses and structural equation models were used to compare structural models and to investigate structural stability and directional effects. Results support the assumption of multidimensionality (i.e., distinct self-concepts for different subjects) and hierarchy with a generic field-of-study-specific self-concept at the apex. Specifying generic field-of-study-specific self-concept as a method factor (i.e., indicated by both subject-specific and field-of-study-specific items) was most consistent with theoretical assumptions. The structural model was invariant over the first months at university. Generic field-of-study-specific self-concept and subject-specific self-concepts largely developed independently from one another. The results emphasize the recently suggested conceptualization of generic self-concept as a method factor to reflect self-concept hierarchy. Self-concepts were structurally stable over time. Several significant horizontal effects (i.e., stability within subjects) suggest that students align their self-concepts closely to the curriculum they encounter in educational contexts and, therefore, may benefit from ample feedback on their performance to develop appropriate subject-specific self-concepts.

ARBITRARY WITHHOLDING OF CONSENT TO HUMANITARIAN ASSISTANCE IN SITUATIONS OF DISASTER

2015 ◽  
Vol 64 (3) ◽  
pp. 501-531 ◽  
Author(s):  
Sandesh Sivakumaran
Keyword(s):  
Large Scale ◽  
Humanitarian Assistance ◽  
The State ◽  
Medical Assistance ◽  
State Practice ◽  
Subject Specific ◽  
Food Shortages ◽  
External Assistance ◽  
The Subject

AbstractFollowing a large-scale disaster, such as a major earthquake, tsunami or cyclone, tens of thousands of persons are often displaced, suffer from food shortages and in need of medical assistance. In situations in which the State affected by the disaster does not meet the needs of the affected persons itself, humanitarian assistance from outside the State might be required. This article considers the role of consent to external humanitarian assistance on the part of the affected State. As there is no single overarching treaty in the area of humanitarian assistance in situations of disaster, the article explores the role of consent in the various disaster-specific, subject-specific and region-specific treaties as well as in the soft law instruments in the area. Although the instruments take seemingly different approaches to the subject, a common standard is identified, namely that consent on the part of the affected State is required before external assistance can be provided but that consent cannot be arbitrarily withheld. The article then goes on to give content to the arbitrary withholding standard, breaking it down into its substantive and procedural elements. These include the meaning of the term ‘arbitrary’; the requirement to provide a reason for the withholding of consent; legitimate grounds for withholding consent; and the actor that assesses the justification. Regard is had for State practice in the context of disasters as well as other areas of the law in which similar tests are used.

Structural equation modelling with complex sampling designs and non-random attrition: A tutorial using lavaan and Mplus

2021 ◽  
Author(s):  
Aja Louise Murray ◽  
Anastasia Ushakova ◽  
Helen Wright ◽  
Tom Booth ◽  
Peter Lynn
Keyword(s):  
Structural Equation ◽  
Large Scale ◽  
Structural Equation Models ◽  
Cluster Sampling ◽  
Complex Sampling ◽  
Latent Trajectory ◽  
Adequate Sampling ◽  
Complex Sampling Designs ◽  
Selection Probabilities ◽  
Pseudo Maximum Likelihood

Complex sampling designs involving features such as stratification, cluster sampling, and unequal selection probabilities are often used in large-scale longitudinal surveys to improve cost-effectiveness and ensure adequate sampling of small or under-represented groups. However, complex sampling designs create challenges when there is a need to account for non-random attrition; a near inevitability in social science longitudinal studies. In this article we discuss these challenges and demonstrate the application of weighting approaches to simultaneously account for non-random attrition and complex design in a large UK-population representative survey. Using an auto-regressive latent trajectory model with structured residuals (ALT-SR) to model the relations between relationship satisfaction and mental health in the Understanding Society study as an example, we provide guidance on implementation of this approach in both R and Mplus is provided. Two standard error estimation approaches are illustrated: pseudo-maximum likelihood robust estimation and Bootstrap resampling. A comparison of unadjusted and design-adjusted results also highlights that ignoring the complex survey designs when fitting structural equation models can result in misleading conclusions.

scholarly journals Genetic heterogeneity in self-reported depressive symptoms identified through genetic analyses of the PHQ-9

2019 ◽  
Vol 50 (14) ◽  
pp. 2385-2396 ◽  
Author(s):  
Jackson G. Thorp ◽  
Andries T. Marees ◽  
Jue-Sheng Ong ◽  
Jiyuan An ◽  
Stuart MacGregor ◽  
...  
Keyword(s):  
Depressive Symptoms ◽  
Genetic Heterogeneity ◽  
Structural Equation ◽  
Large Scale ◽  
Clinical Symptoms ◽  
Factor Model ◽  
Genetic Correlations ◽  
Genetic Covariance ◽  
Association Analyses ◽  
Genome Wide

AbstractBackgroundDepression is a clinically heterogeneous disorder. Previous large-scale genetic studies of depression have explored genetic risk factors of depression case–control status or aggregated sums of depressive symptoms, ignoring possible clinical or genetic heterogeneity.MethodsWe analyse data from 148 752 subjects of white British ancestry in the UK Biobank who completed nine items of a self-rated measure of current depressive symptoms: the Patient Health Questionnaire (PHQ-9). Genome-Wide Association analyses were conducted for nine symptoms and two composite measures. LD Score Regression was used to calculate SNP-based heritability (h2SNP) and genetic correlations (rg) across symptoms and to investigate genetic correlations with 25 external phenotypes. Genomic structural equation modelling was used to test the genetic factor structure across the nine symptoms.ResultsWe identified nine genome-wide significant genomic loci (8 novel), with no overlap in loci across symptoms. h2SNP ranged from 6% (concentration problems) to 9% (appetite changes). Genetic correlations ranged from 0.54 to 0.96 (all p < 1.39 × 10−3) with 30 of 36 correlations being significantly smaller than one. A two-factor model provided the best fit to the genetic covariance matrix, with factors representing ‘psychological’ and ‘somatic’ symptoms. The genetic correlations with external phenotypes showed large variation across the nine symptoms.ConclusionsPatterns of SNP associations and genetic correlations differ across the nine symptoms, suggesting that current depressive symptoms are genetically heterogeneous. Our study highlights the value of symptom-level analyses in understanding the genetic architecture of a psychiatric trait. Future studies should investigate whether genetic heterogeneity is recapitulated in clinical symptoms of major depression.

scholarly journals A Practical Guide for Analyzing Large-Scale Assessment Data Using Mplus: A Case Demonstration Using the Program for International Assessment of Adult Competencies Data

2020 ◽  
pp. 107699862097855
Author(s):  
Takashi Yamashita ◽  
Thomas J. Smith ◽  
Phyllis A. Cummins
Keyword(s):  
Structural Equation ◽  
Large Scale ◽  
Structural Equation Models ◽  
Preparation Process ◽  
Data Preparation ◽  
Assessment Data ◽  
Statistical Software ◽  
Large Scale Assessment ◽  
Scale Assessment ◽  
International Assessment

In order to promote the use of increasingly available large-scale assessment data in education and expand the scope of analytic capabilities among applied researchers, this study provides step-by-step guidance, and practical examples of syntax and data analysis using Mplus. Concise overview and key unique aspects of large-scale assessment data from the 2012/2014 Program for International Assessment of Adult Competencies (PIAAC) are described. Using commonly-used statistical software including SAS and R, a simple macro program and syntax are developed to streamline the data preparation process. Then, two examples of structural equation models are demonstrated using Mplus. The suggested data preparation and analytic approaches can be immediately applicable to existing large-scale assessment data.

Exploring Factor Model Parameters across Continuous Variables with Local Structural Equation Models

2016 ◽  
Vol 51 (2-3) ◽  
pp. 257-258 ◽  
Author(s):  
Andrea Hildebrandt ◽  
Oliver Lüdtke ◽  
Alexander Robitzsch ◽  
Christopher Sommer ◽  
Oliver Wilhelm
Keyword(s):  
Structural Equation ◽  
Structural Equation Models ◽  
Factor Model ◽  
Model Parameters ◽  
Continuous Variables

scholarly journals Hydraulic diversity stabilizes productivity in a large-scale subtropical tree biodiversity experiment

2021 ◽  
Author(s):  
Florian Schnabel ◽  
Xiaojuan Liu ◽  
Matthias Kunz ◽  
Kathryn E. Barry ◽  
Franca J. Bongers ◽  
...  
Keyword(s):  
Climate Change ◽  
Species Richness ◽  
Tree Species ◽  
Structural Equation ◽  
Large Scale ◽  
Structural Equation Models ◽  
Forest Productivity ◽  
Climate Mitigation ◽  
Climate Change Effects ◽  
Tree Species Richness

AbstractExtreme climatic events threaten forests and their climate mitigation potential globally. Understanding the drivers promoting ecosystems stability is therefore considered crucial to mitigate adverse climate change effects on forests. Here, we use structural equation models to explain how tree species richness, asynchronous species dynamics and diversity in hydraulic traits affect the stability of forest productivity along an experimentally manipulated biodiversity gradient ranging from 1 to 24 tree species. Tree species richness improved stability by increasing species asynchrony. That is at higher species richness, inter-annual variation in productivity among tree species buffered the community against stress-related productivity declines. This effect was mediated by the diversity of species’ hydraulic traits in relation to drought tolerance and stomatal control, but not the community-weighted means of these traits. Our results demonstrate important mechanisms by which tree species richness stabilizes forest productivity, thus emphasizing the importance of hydraulically diverse, mixed-species forests to adapt to climate change.

scholarly journals Achievements and perspectives of development of Eastern Slavonic explanatory linguistic terminography

2017 ◽  
pp. 40-53
Author(s):  
Vyacheslav Shcherbin
Keyword(s):  
Comparative Analysis ◽  
Linguistic Terms ◽  
General Science ◽  
The West ◽  
Scientific Terminology ◽  
Subject Specific ◽  
The Subject ◽  
Specialized Texts ◽  
Further Development ◽  
Level Of Analysis

The most complete explanatory dictionaries of linguistic terminology published in Eastern Slavonic countries are considered in the article. The comparative analysis of index, micro-, macro-, and megastructural characteristics of the most complete Russian, Ukrainian, and Belarusian dictionaries of linguistic terms (by O.S. Akhmanova, M.G. Bulakhov, and A.A. Zagnitko) is conducted. The forecast is made about perspectives and possible ways of development of Eastern Slavonic explanatory linguistic terminography. The conclusion is substantiated that a much higher informational level of analysis of the metalanguages of Russian, Ukrainian and Belarusian linguistics can be reached only if a combined explanatory dictionary of Eastern Slavic linguistic terminology is created by mutual efforts of the linguists, lexicographers and terminologists of Russia, Ukraine, and Belarus. In its turn, the unresolved problems of the modern Eastern Slavonic explanatory linguistic terminography should include the following issues: 1) there is a clearly insufficient level of institutionalization of the terminography activity in some Eastern Slavonic countries (in Belarus, for example, until now, there are no specialized centers, departments and periodicals whose main purpose would be studying, systematizing and dictionary-coding scientific terminology revealed as a result of analysis of scientific and specialized texts); 2) drafting of the Eastern Slavonic explanatory linguistic terminography products shows certain negative trends (many terminological and encyclopedic dictionaries and reference books lack alphabetic and subject-specific indexes of 12 terms that are much-needed for the readers; a number of terminological dictionaries on linguistics are clearly compilations). In addition, there is a vital need for the Eastern Slavonic linguistic terminologists to cooperate with the subject-specialists in the different branches of modern linguistics as actively as possible to address the topical issues of the current terminography practices. If this closest union of terminologists and subjectspecialists in the different branches of modern linguistics is not be established in the nearest future, then, apparently, terminography and the science of terminology will stop coordinating their professional efforts with the general science of philology soon, and further development of these cross-cutting disciplines will go its own way as this is already going on in some countries of the West.

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