scholarly journals Predicting Language Outcomes for Children Learning Augmentative and Alternative Communication: Child and Environmental Factors

2013 ◽  
Vol 56 (5) ◽  
pp. 1595-1612 ◽  
Author(s):  
Nancy C. Brady ◽  
Kathy Thiemann-Bourque ◽  
Kandace Fleming ◽  
Kris Matthews
Keyword(s):  
Augmentative And Alternative Communication ◽  
Latent Variable ◽  
Structural Equation ◽  
Communication Complexity ◽  
Equation Model ◽  
Preschool Age ◽  
Outcome Variable ◽  
Alternative Communication ◽  
Outcomes For Children ◽  
At Home

Purpose To investigate a model of language development for nonverbal preschool-age children learning to communicate with augmentative or alternative communication. Method Ninety-three preschool children with intellectual disabilities were assessed at Time 1, and 82 of these children were assessed 1 year later, at Time 2. The outcome variable was the number of different words the children produced (with speech, sign, or speech-generating devices). Children's intrinsic predictor for language was modeled as a latent variable consisting of cognitive development, comprehension, play, and nonverbal communication complexity. Adult input at school and home, and amount of augmentative or alternative communication instruction, were proposed mediators of vocabulary acquisition. Results A confirmatory factor analysis revealed that measures converged as a coherent construct, and a structural equation model indicated that the intrinsic child predictor construct predicted different words children produced. The amount of input received at home, but not at school, was a significant mediator. Conclusions The hypothesized model accurately reflects a latent construct of Intrinsic Symbolic Factor (ISF). Children who evidenced higher initial levels of ISF and more adult input at home produced more words 1 year later. The findings support the need to assess multiple child variables and suggest interventions directed to the indicators of ISF and input.

Valuing the Media: Access and Autonomy as Functions of Legitimacy for Journalists

2015 ◽  
Vol 8 (1) ◽  
pp. 46-67 ◽  
Author(s):  
David Welch Suggs
Keyword(s):  
Social Media ◽  
Intercollegiate Athletics ◽  
Latent Variable ◽  
Structural Equation ◽  
Equation Model ◽  
Media Access ◽  
Sports Organizations ◽  
The Past ◽  
Digital Era ◽  
The Media

Sports reporters depend on access to events and sources as much or more than any other news professional. Over the past few years, some sports organizations have attempted to restrict such access, as well as what reporters can publish via social media. In the digital era, access and publishing autonomy, as institutionalized concepts, are evolving rapidly. Hypotheses tying access and work practices to reporters’ perceptions of the legitimacy they experience are developed and tested via a structural equation model, using responses to a survey of journalists in American intercollegiate athletics and observed dimensions of access and autonomy to measure a latent variable of legitimacy. The model suggests that reporters have mixed views about whether they possess the legitimacy they need to do their jobs.

Modelling Museum Visitors’ Perception and Experience of Authenticity: Examining Heterogeneity with a Finite Mixture Model

2021 ◽  
Vol 56 ◽  
pp. 0-0
Author(s):  
Claudia Bauer-Krösbacher ◽  
Josef Mazanec
Keyword(s):  
Latent Variable ◽  
Structural Equation ◽  
Latent Class ◽  
Structural Model ◽  
Unobserved Heterogeneity ◽  
Model Fitting ◽  
Equation Model ◽  
Finite Mixture ◽  
Museum Visitors ◽  
Specific Strength

Purpose. In this study, the authors explore the role of museum visitors’ perceptions and experiences of authenticity. They introduce several variants of authenticity experience and analyse how they are intertwined and feed visitor satisfaction. Method. The authors apply a multi-step model fitting and validation procedure including inferred causation methods and finite mixture modelling to verify whether the visitors’ perceptions of authenticity are subject to unobserved heterogeneity. They elaborate an Authenticity Model that demonstrates out-of-sample validity and generalisability by being exposed to new data for another cultural attraction in another city. Then, they address the heterogeneity hypothesis and evaluate it for the case study with the larger sample. Findings. In both application cases, the Sisi museum in Vienna and the Guinness Storehouse in Dublin, the empirical results support the assumed cause-effect sequence, translating high quality information display—from traditional and multimedia sources—into Perceived Authenticity and its experiential consequences such as Depth and Satisfaction. Accounting for unobserved heterogeneity detects three latent classes with segment-specific strength of relationships within the structural model. Research and conclusions limitations. The combined latent-class, structural-equation model needs validation with another sample that would have to be larger than the available Guinness database. Future studies will have to complement the purely data-driven search for heterogeneity with theory-guided reasoning about potential causes of diversity in the strength of the structural relationships. Practical implications. Cultural heritage sites are among the attractions most typical of city tourism. History tends to materialise in the artefacts accumulated by the population among the urban agglomerations, and museums are the natural places for preserving exhibits of cultural value. Authenticity must be considered an important quality assessment criterion for many visitors, whereby, the distinction between object authenticity and existential authenticity is crucial. Originality. In addition to making substantive contributions to authenticity theory, the authors also extend previous research in terms of methodological effort. Authenticity research, so far, has neither exploited inferred causation methods nor combined latent variable modelling with detecting unobserved heterogeneity. Type of paper: Research article.

Managerial Antecedents and Individual Consequences of Group Cohesiveness in Travel Service Selling

1997 ◽  
Vol 35 (4) ◽  
pp. 56-63 ◽  
Author(s):  
Kenneth R. Bartkus ◽  
Roy D. Howell ◽  
C. R. Michael Parent ◽  
Cathy L. Hartman
Keyword(s):  
Latent Variable ◽  
Structural Equation ◽  
Role Stress ◽  
Equation Model ◽  
Group Cohesiveness ◽  
Travel Agents ◽  
Management Actions ◽  
Managerial Implications ◽  
Task Oriented ◽  
The Relationship

A latent variable structural equation model describing the relationship between managerial actions, group cohesiveness, and selected job-related outcomes was developed and tested using a sample of travel agents. The results of the analysis indicated that cohesiveness influences a variety of salient outcomes, including organizational commitment, job satisfaction, motivation, and role stress. Consistent with some prior research, the relationship between cohesiveness and selling performance was not significant. The results also showed that management actions in the form of task-oriented and relationship-oriented leadership directly influence cohesiveness. Managerial implications are discussed.

scholarly journals Estimating Three-way Latent Interaction Effects in Structural Equation Modeling

2016 ◽  
Vol 5 (6) ◽  
pp. 73
Author(s):  
Birhanu Worku Urge ◽  
Kepher Makambi ◽  
Anthony Wanjoya
Keyword(s):  
Sample Size ◽  
Structural Equation Model ◽  
Interaction Effect ◽  
Latent Variable ◽  
Structural Equation ◽  
Error Control ◽  
Equation Model ◽  
Equation Modeling ◽  
Type I ◽  
Nonlinear Structural Equation

A Monte Carlo simulation was performed for estimating and testing hypotheses of three-way interaction effect in latent variable regression models. A considerable amount of research has been done on estimation of simple interaction and quadratic effect in nonlinear structural equation. The present study extended to three-way continuous latent interaction in structural equation model. The latent moderated structural equation (LMS) approach was used to estimate the parameters of the three-way interaction in structural equation model and investigate the properties of the method under different conditions though simulations. The approach showed least bias, standard error,and root mean square error as indicator reliability and sample size increased. The power to detect interaction effect and type I error control were also manipulated showing that power increased as interaction effect size, sample size and latent covariance increased.

scholarly journals Impact of Market Orientation Components on Organizational Performance of SMEs. The single-industry approach " Food and Beverage Sector"

2021 ◽  
Vol 8 (5) ◽  
pp. 504-516
Author(s):  
Akram Abdulsamad ◽  
Noor Azman ALI ◽  
Anuar Shah Bali Mahomed ◽  
Haslinda Hashim ◽  
Abdulwahab Jandab ◽  
...  
Keyword(s):  
Organizational Performance ◽  
Market Orientation ◽  
Latent Variables ◽  
Latent Variable ◽  
Structural Equation ◽  
Customer Orientation ◽  
Equation Model ◽  
Food And Beverage ◽  
Competitor Orientation ◽  
Main Components

This study examines the direct effect of the three main components of the market orientation on the organizational performance of SMEs in Yemen. Four variables are used in the research, are competitor orientation, customer orientation, and inter-functional coordination, as the exogenous latent variables, whereas organizational performance, as the endogenous latent variable. The quantitative approach is applied in this study with causal and descriptive research. The single-sector method is adopted, is the food and beverage sector, by using random sample sampling, the sample size was 640 managers/owners. only 459 samples were valid to conduct the analysis by using the Structural Equation Model (SEM) in SmartPLS Software version 3.0. The findings of the study reveal that the three main components of the market orientation have a positive and significant impact on SMEs' organizational performance. However, the effect size of customer orientation on organizational performance was more than competitor orientation and inter-functional coordination.

scholarly journals Products of Variables in Structural Equation Models: Multiplicative Reticular Action Models

2019 ◽  
Author(s):  
Steven M. Boker ◽  
Timo von Oertzen ◽  
Andreas Markus Brandmaier
Keyword(s):  
Latent Variables ◽  
Latent Variable ◽  
Structural Equation ◽  
Structural Equation Models ◽  
Equation Model ◽  
Random Coefficients ◽  
Action Model ◽  
Action Models ◽  
Special Case ◽  
General Method

A general method is introduced in which variables that are products of other variables in the context of a structural equation model (SEM) can be decomposed into the sources of variance due to the multiplicands. The result is a new category of SEM which we call a Multiplicative Reticular Action Model (XRAM). XRAM can include interactions between latent variables, multilevel random coefficients, latent variable moderators, and novel constructs such as factors of paths and twin genetic decomposition of multilevel random coefficients. The method relies on an assumption that all variance sources in a model can be decomposed into linear combinations of independent normal standardized variables. Although the distribution of a variable that is an outcome of multiplication between other variables is not normal, the assumption is that it can be decomposed into sources that are normal if one takes into account the non-normality induced by the multiplication. The method is applied to an example to show how in a special case it is equivalent to known unbiased and efficient estimators in the statistical literature. Two simulations are presented that demonstrate the precision of the approximation and implement the method to estimate parameters in a multilevel autoregressive framework.

Sequenced Ordered Logit Model Considering Latent Variables for Determining Trip Satisfaction of Metro Passengers

2020 ◽  
Vol 2674 (9) ◽  
pp. 755-766
Author(s):  
Tara Saeidi ◽  
Mahmoud Mesbah ◽  
Meeghat Habibian
Keyword(s):  
Public Transportation ◽  
Latent Variables ◽  
Logit Model ◽  
Latent Variable ◽  
Structural Equation ◽  
Equation Model ◽  
Access Time ◽  
Ordered Logit ◽  
Ordered Logit Model ◽  
Passenger Satisfaction

Improving the public transportation system to compete with the private modes requires an understanding of passenger perceptions of the service quality (SQ). In the literature, various models have been developed to identify effective SQ attributes and to assess their relationship with passenger satisfaction. However, most of them either ignore the socioeconomic and trip characteristics or consider them by a market segmentation approach. Since these variables can affect passenger perceptions, it is important to include them in the model. This paper aims to capture the effect of socioeconomic and trip variables by combining them with SQ attributes in a satisfaction analysis. An ordered logit model considering SQ latent variables is calibrated to model passenger satisfaction. The measurement part of a Structural Equation Model (SEM) is applied to construct latent variable structures. The case study was on the Tehran metro. The SQ attributes were used to form five SQ latent variables: “comfort,”“information,”“cleanliness,”“service,” and “safety/security.” The results indicate that socioeconomic and trip characteristics, as well as the SQ latent variables, had a significant effect on passenger satisfaction. From the results of this study, “service” and “comfort” were found to be the most effective contributors to satisfaction levels among the SQ latent variables. Among socioeconomic and trip characteristics, gender, education, driving license, egress mode, access time, and trip origin type (i.e., work, education, etc.) were also important in passenger satisfaction.

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