The twain shall meet: Uniting the analysis of sex differences and within-sex variation

1996 ◽  
Vol 19 (2) ◽  
pp. 262-262
Author(s):  
David C. Rowe
Keyword(s):  
Sex Differences ◽  
Structural Equation Modeling ◽  
Statistical Methods ◽  
Research Design ◽  
Environmental Effects ◽  
Structural Equation ◽  
Differentially Expressed ◽  
Equation Modeling ◽  
Mathematical Abilities ◽  
Males And Females

AbstractSpatial and mathematical abilities may be “sex-limited” traits. A sex-limited trait has the same determinants of variation within the sexes, but the genetic or environmental effects would be differentially expressed in males and females. New advances in structural equation modeling allow means and variation to be estimated simultaneously. When these statistical methods are combined with a genetically informative research design, it should be possible to demonstrate that the genes influencing spatial and mathematical abilities are sex-limited in their expression. This approach would give an empirical confirmation of Geary's evolutionary speculations.

scholarly journals Structure-Behavior Coalescence Design to Improve the Modifiability of Home Care IoT System

2021 ◽  
Vol 15 ◽  
pp. 1759-1765
Author(s):  
Shuh-Ping Sun ◽  
William S. Chao
Keyword(s):  
Structural Equation Modeling ◽  
Home Care ◽  
Statistical Methods ◽  
Structural Equation ◽  
Systems Development ◽  
Flow Diagram ◽  
Equation Modeling ◽  
Computer Algorithms ◽  
Key Factor ◽  
Main Factors

Modifiability improvement is a key factor in the successful Home Care IoT System (HCIS) systems development. It includes disciplined system layering (DSL), well-defined components (WDC), published interface (PI), and well-defined behavior (WDB) which represent the four main factors that enhance the modifiability of HCIS. Structure-Behavior Coalescence (SBC) method uses three fundamental diagrams: a) framework diagram, b) component operation diagram, and c) interaction flow diagram to accomplish the design of HCIS. Through framework diagram, Structure-Behavior Coalescence design of HCIS demonstrates tremendous effects of disciplined system layering. Through component operation diagram, Structure-Behavior Coalescence design of HCIS demonstrates large effects of well-defined components and published interfaces. Through interaction flow diagram, Structure-Behavior Coalescence design of HCIS demonstrates tremendous effects of well-defined behaviors. Structural Equation Modeling (SEM) refers to a diverse set of unrelated computer algorithms and statistical methods, which are suitable for constructing networks for analysis. Applied SEM method can verify that Structure-Behavior Coalescence design is be able to enhance the Modifiability of HCIS.

scholarly journals A National Swedish Twin-Sibling Study of Alcohol Use Disorders

2016 ◽  
Vol 19 (5) ◽  
pp. 430-437 ◽  
Author(s):  
Kenneth S. Kendler ◽  
MirNabi PirouziFard ◽  
Sara Lönn ◽  
Alexis C. Edwards ◽  
Hermine H. Maes ◽  
...  
Keyword(s):  
Risk Factors ◽  
Sex Differences ◽  
Alcohol Use ◽  
Environmental Effects ◽  
Environmental Risk ◽  
Structural Equation ◽  
Alcohol Use Disorders ◽  
Twin Studies ◽  
Environmental Risk Factors ◽  
Equation Modeling

The relationship between the genetic and environmental risk factors for alcohol use disorders (AUD) detected in Swedish medical, pharmacy, and criminal registries has not been hitherto examined. Prior twin studies have varied with regard to the detection of shared environmental effects and sex differences in the etiology of AUD. In this report, structural equation modeling in OpenMx was applied to (1) the three types of alcohol registration in a population-based sample of male–male twins and reared-together full and half siblings (total 208,810 pairs), and (2) AUD, as a single diagnosis, in male–male, female–female, and opposite-sex (OS) twins and reared-together full and half siblings (total 787,916 pairs). An independent pathway model fit best to the three forms of registration and indicated that between 70% and 92% of the genetic and 63% and 98% of the shared environmental effects were shared in common with the remainder unique to each form of AUD registration. Criminal registration had the largest proportion of unique genetic and environmental factors. The best fit model for AUD estimated the heritability to be 22% and 57%, respectively, in females and males. Both shared (12% vs. 6%) and special twin environment (29% vs. 2%) were substantially more important in females versus males. In conclusion, AUD ascertained from medical, pharmacy, and criminal Swedish registries largely share the same genetic and environmental risk factors. Large sex differences in the etiology of AUD were seen in this sample, with substantially stronger familial environmental and weaker genetic effects in females versus males.

Longitudinal Structural Equation Modeling in Lifespan Developmental Analyses

2019 ◽  
Author(s):  
Philip Parker ◽  
Robert Brockman
Keyword(s):  
Structural Equation Modeling ◽  
Research Design ◽  
Structural Equation ◽  
Research Question ◽  
Equation Modeling ◽  
Latent Growth ◽  
Longitudinal Structural Equation Modeling ◽  
Diary Studies ◽  
Careful Specification ◽  
The Right

Longitudinal structural equation modeling (LSEM) is used to answer lifespan relevant questions such as (a) what is the effect of one variable on change in and other, (b) what is the average trajectory or growth rate of some psychological variable, and (c) what variability is there in average trajectories and what predicts this variability. The first of these questions is often answered by a LSEM called an autoregressive cross-lagged (ACL) model. The other two questions are most typically answered by an LSEM called a latent growth curve (LGC). These models can be applied to a few time waves (measured over several years) or to many time waves (such as present in diary studies) and can be altered, expanded, or even integrated. However, decisions on what model to use must be driven by the research question. The right tool for the job is not always the most complex. And, more importantly, the right tool must be matched to the best possible research design. Sometimes in lifespan research the right tool is LSEM. However, researchers should prioritize research design as well as careful specification of the processes and mechanisms they are interested in rather than simply choosing the most complicated LSEM they can find.

A Test of the Sport Commitment Model Using Structural Equation Modeling

1993 ◽  
Vol 15 (2) ◽  
pp. 119-133 ◽  
Author(s):  
Paul J. Carpenter ◽  
Tara K. Scanlan ◽  
Jeffery P. Simons ◽  
Marci Lobel
Keyword(s):  
Structural Equation Modeling ◽  
Structural Equation ◽  
Team Sports ◽  
Social Constraints ◽  
Equation Modeling ◽  
Sport Commitment ◽  
Modeling Analysis ◽  
Proposed Model ◽  
Initial Hypothesis ◽  
Males And Females

This article presents the results of a structural equation modeling analysis of the Sport Commitment Model. This model proposes that commitment is determined by sport enjoyment, involvement alternatives, personal investments, social constraints, and involvement opportunities. Preliminary analyses demonstrated that the model was applicable to both younger (< 12 years old) and older (> 13 years old) athletes, to males and females, and to three different team sports. Structural equation modeling results demonstrated that the proposed model was a good fit of the data (CFI = .981), with the findings accounting for 68% of the commitment variance. As predicted, greater sport enjoyment, involvement opportunities, and the personal investments of time and effort led to greater commitment. Counter to our initial hypothesis, commitment was negatively related to social constraints. Measurement problems led to the involvement alternatives component being excluded from tests of the model presented here, but not from the theoretical model.

scholarly journals The Nexus of the Dark Triad Personality Traits With Cyberbullying, Empathy, and Emotional Intelligence: A Structural-Equation Modeling Approach

2021 ◽  
Vol 12 ◽  
Author(s):  
Estelle C. Schade ◽  
Martin Voracek ◽  
Ulrich S. Tran
Keyword(s):  
Emotional Intelligence ◽  
Sex Differences ◽  
Structural Equation Modeling ◽  
Personality Traits ◽  
Lower Order ◽  
Structural Equation ◽  
Community Sample ◽  
Dark Triad ◽  
Equation Modeling ◽  
Future Research

This study set out to elucidate the complex suite of associations between the Dark Triad personality traits (Machiavellianism, narcissism, and psychopathy), emotional intelligence, empathy, and cyberbullying, as the respective findings regarding this topic have been inconsistent. Studies preponderantly have relied on abbreviated Dark Triad measures that do not differentiate between its lower-order facets. Further, most extant studies have exclusively been based on female psychology undergraduates and have not accounted for known sex differences on the Dark Triad traits and cyberbullying, or for negative associations between cyberbullying and age. Therefore, this nexus of interrelations was investigated in a diverse community sample (N = 749). A structural equation-modeling approached was used to examine predictors of cyberbullying and to test for mediating relationships between lower-order Dark Triad facets and emotional intelligence and empathy. Multigroup models were applied to test for sex-specific patterns. Empathy did not predict cyberbullying, whereas emotional intelligence partly mediated the Dark Triad associations with cyberbullying among both sexes. Sex-specific patterns in the associations between Dark Triad traits and cyberbullying were particularly observed for the grandiose and vulnerable narcissism facets. Emotional intelligence appeared to buffer effects of grandiose narcissism on cyberbullying. Future research could fruitfully explore cyberbullies’ profiles regarding primary and secondary psychopathy, sex differences in narcissism, and buffering effects of emotional intelligence. Further improvements regarding the measurement of dark personality traits are indicated as well.

scholarly journals ASSESSING ENTERPRISER PROFILES ON ENTREPRENEURIAL MANAGERIAL ACTIVITIES IN ELDORET, KENYA

2020 ◽  
Vol 5 (12) ◽  
pp. 368-376
Author(s):  
Mary Nyiva Mwaniki ◽  
Lydia Maket
Keyword(s):  
Multivariate Analysis ◽  
Structural Equation Modeling ◽  
Sample Size ◽  
Research Design ◽  
Failure Rate ◽  
Structural Equation ◽  
Target Population ◽  
Measurement Model ◽  
Equation Modeling ◽  
Enterprise Success

The purpose of this research is to analysis of enterpriser profiles on entrepreneurial managerial in Bungoma, Kenya .Efforts have been made to support entrepreneurial managerial activities training and the provision of consultative services; interestingly, the failure rate still remains high Neither research on the entrepreneur personality nor enterpriser profiles have demonstrated a decisive influence on entrepreneurial managerial activities. The study adopted a post-positivism research , with  research design of explanatory survey .The target population and sample size  were adopted from a thesis selected  from Eldoret, Towns .Data was analyzed quantitatively using techniques such as: Multivariate analysis, structural equation modeling. Finding indicates:  entrepreneurial competencies, mentoring, enterpriser profile and enterprise success dimensions were sufficiently reliable and valid to be included in the subsequent model testing. The measurement model results suggest that the model provides a reasonably good fit and thus it was suitable .The CFA results supported the measurement model.

scholarly journals ANALYSIS OF THE EFFECTS OF PERCEIVED BENEFIT AND PERCEIVED EASE ON CONSUMER INTEREST IN USING SINGLE TRIP TICKET OF MRT JAKARTA AND THE IMPACT ON BUYING DECISION

2020 ◽  
Vol 2 (1) ◽  
pp. 70-80
Author(s):  
Kadita Ayuverda ◽  
Dudi Permana
Keyword(s):  
Structural Equation Modeling ◽  
Research Design ◽  
Structural Equation ◽  
Sampling Technique ◽  
Equation Modeling ◽  
Survey Method ◽  
Consumer Interest ◽  
Descriptive Research ◽  
Perceived Benefit ◽  
The Impact

The purpose of the present study was determining the result of Analysis of the Effects of Perceived Benefit and Perceived Ease on Consumer Buying Interest in Single Trip Ticket of MRT Jakarta and the Impact on Buying Decision. The present study used descriptive research design with survey method. Sampling used purposive sampling technique. The present study was tested using structural equation modeling – Lisrel to examine the effect of significance of the entire model and preset path. The finding showed that Perceived Benefit and Perceived Ease significantly affected Consumer Buying Interest. The present study also showed that Consumer Buying Interest affected Buying Decision. The company should improve Perceived Benefit and Perceived Ease.

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