scholarly journals A Hybrid Scan Gibbs Sampler for Bayesian Models with Latent Variables

2021 ◽  
Vol 36 (3) ◽  
Author(s):  
Grant Backlund ◽  
James P. Hobert ◽  
Yeun Ji Jung ◽  
Kshitij Khare
Keyword(s):  
Gibbs Sampler ◽  
Latent Variables ◽  
Bayesian Models

Inference for nonconjugate Bayesian Models using the Gibbs sampler

1991 ◽  
Vol 19 (4) ◽  
pp. 399-405 ◽  
Author(s):  
Bradley P. Carlin ◽  
Nicholas G. Polson
Keyword(s):  
Gibbs Sampler ◽  
Bayesian Models

scholarly journals Bayesian paired comparison with the bpcs package

2021 ◽  
Author(s):  
David Issa Mattos ◽  
Érika Martins Silva Ramos
Keyword(s):  
Posterior Distribution ◽  
Latent Variables ◽  
Type I Error ◽  
Paired Comparison ◽  
Bayesian Models ◽  
R Package ◽  
Type I ◽  
Online Appendix ◽  
Credible Intervals ◽  
Comparison Data

AbstractThis article introduces the R package (Bayesian Paired Comparison in Stan) and the statistical models implemented in the package. This package aims to facilitate the use of Bayesian models for paired comparison data in behavioral research. Bayesian analysis of paired comparison data allows parameter estimation even in conditions where the maximum likelihood does not exist, allows easy extension of paired comparison models, provides straightforward interpretation of the results with credible intervals, has better control of type I error, has more robust evidence towards the null hypothesis, allows propagation of uncertainties, includes prior information, and performs well when handling models with many parameters and latent variables. The package provides a consistent interface for R users and several functions to evaluate the posterior distribution of all parameters to estimate the posterior distribution of any contest between items and to obtain the posterior distribution of the ranks. Three reanalyses of recent studies that used the frequentist Bradley–Terry model are presented. These reanalyses are conducted with the Bayesian models of the package, and all the code used to fit the models, generate the figures, and the tables are available in the online appendix.

Probability-Based and Measurement-Related Hypotheses With Full Restriction for Investigations by Means of Confirmatory Factor Analysis

Methodology ◽  
2011 ◽  
Vol 7 (4) ◽  
pp. 157-164
Author(s):  
Karl Schweizer
Keyword(s):  
Factor Analysis ◽  
Confirmatory Factor Analysis ◽  
Cognitive Processing ◽  
Latent Variables ◽  
Repeated Measures ◽  
Latent Variable ◽  
Model Fit ◽  
Repeated Measures Data ◽  
Confirmatory Factor ◽  
And Performance

Probability-based and measurement-related hypotheses for confirmatory factor analysis of repeated-measures data are investigated. Such hypotheses comprise precise assumptions concerning the relationships among the true components associated with the levels of the design or the items of the measure. Measurement-related hypotheses concentrate on the assumed processes, as, for example, transformation and memory processes, and represent treatment-dependent differences in processing. In contrast, probability-based hypotheses provide the opportunity to consider probabilities as outcome predictions that summarize the effects of various influences. The prediction of performance guided by inexact cues serves as an example. In the empirical part of this paper probability-based and measurement-related hypotheses are applied to working-memory data. Latent variables according to both hypotheses contribute to a good model fit. The best model fit is achieved for the model including latent variables that represented serial cognitive processing and performance according to inexact cues in combination with a latent variable for subsidiary processes.

Meta-Accuracy and Perceived Reciprocity From the Perception-Meta-Perception Social Relations Model

2019 ◽  
Vol 50 (1) ◽  
pp. 24-37
Author(s):  
Ben Porter ◽  
Camilla S. Øverup ◽  
Julie A. Brunson ◽  
Paras D. Mehta
Keyword(s):  
Structural Equation Modeling ◽  
Social Relations ◽  
Latent Variables ◽  
Structural Equation ◽  
Multilevel Structural Equation Modeling ◽  
Equation Modeling ◽  
Complete Understanding ◽  
Social Relations Model ◽  
Flexible Framework ◽  
Multilevel Structural Equation

Abstract. Meta-accuracy and perceptions of reciprocity can be measured by covariances between latent variables in two social relations models examining perception and meta-perception. We propose a single unified model called the Perception-Meta-Perception Social Relations Model (PM-SRM). This model simultaneously estimates all possible parameters to provide a more complete understanding of the relationships between perception and meta-perception. We describe the components of the PM-SRM and present two pedagogical examples with code, openly available on https://osf.io/4ag5m . Using a new package in R (xxM), we estimated the model using multilevel structural equation modeling which provides an approachable and flexible framework for evaluating the PM-SRM. Further, we discuss possible expansions to the PM-SRM which can explore novel and exciting hypotheses.

On the measurement of 'latent variables'

2002 ◽  
Author(s):  
Gustavo Mazcorro-Tellez ◽  
Servio T. Guillen Burguete
Keyword(s):  
Latent Variables

ANALYSIS THE IMPACT OF THE IMPLEMENTATION OF QUALITY MANAGEMENT SYSTEM (QMS) AND SAFETY AND HEALTHY AT WORK MANAGEMENT SYSTEM (SHWMS / SMK3) ON THE JOB PERFORMANCE OF EMPLOYEES

2018 ◽  
Vol 3 (01) ◽  
pp. 45
Author(s):  
Nur Hidayat ◽  
Indah Kusuma Hayati
Keyword(s):  
Quality Management ◽  
Job Performance ◽  
Latent Variables ◽  
Management System ◽  
Quality Management System ◽  
Partial Least Square ◽  
Least Square ◽  
Global Challenges ◽  
The Impact ◽  
Work Management

Recently, the evolvement of globalization era has been the global challenges that cannot be avoided either by private or government sectors, and they are requested to be survived encountering such the condition. The implementation of Quality Management System (QMS) in the operational company is the way how to guarantee the quality of products or services offered to the people. One of the purposes of QMS implementation is to provide a prime satisfaction to the customers. The impact of QMS implementation is expected to increase job performance of the employees. Besides the implementation of Quality Management System (QMS), the impact of global challenges has been increasing the competitive efforts to execute more effective production process. However, it has required manpower protection accordingly. This research aims to find out whether the implementation of quality management system and safety and healthy at work management system have impacted on the job performance of employees. Objects of this research are the employees in the production department at PT Guna Senaputra Sejahtera Plant 1 Bogor. Data analysis technique of this research has applied software Smart PLS (Partial Least Square). PLS has estimated a model of correlation among the latent variables and correlation between latent variables and its indicators. Result of data processing has indicated that the implementation of Quality Management System (QMS) and system of safety and healthy at work have positively and significantly impacted job performance of employees.Keywords : Quality Management System (QMS), Safety and Healthy at Work System ( SHWS / SMK3), and Job Performance of Employees

ICT SMEs, Performance, Absorptive Capacity and Transformative Capacity

2019 ◽  
Vol 118 (3) ◽  
pp. 178-188
Author(s):  
Yeon-Sung Cho ◽  
Kyung-Il Khoe
Keyword(s):  
Firm Performance ◽  
Market Orientation ◽  
Empirical Analysis ◽  
Absorptive Capacity ◽  
Latent Variables ◽  
Equation Modeling ◽  
Transformative Capacity ◽  
The Impact ◽  
The Empirical Analysis ◽  
Innovative Capacity

This study intends to integrate the relationship of market orientation, innovative capacity and firm performance to Information and Communication Technology(ICT) SMEs. The purpose of this study is to identify the role of absorptive capacity and transformative capacity that affect the performance of ICT SMEs. Hypotheses were established between five latent variables. A total of six hypotheses were established including the moderated effects of absorptive capacity and transformative capacity. Of the data collected after the survey, 112 valid surveys were selected as the final sample, except for 17 questionnaires with high non - response and insincere response. The empirical analysis of this study used smartpls3.0, Partial Least Squares (PLS), a variance-based structural equation modeling. The empirical analysis of this study revealed that the impact of market orientation on innovative capacity was significant. Moreover, the innovative capacity had a positive effect on the performance of ICT SMEs. In addition, the absorptive activity had a positive moderated effect between the market orientation and the innovative capacity. On the other hand, the transformative capacity showed a positive moderated effect in relation to innovative capacity and firm performance. Our empirical results have demonstrated the importance of knowledge based capacity in the ICT SMEs.

Conceptualizing Protective Family Context and Its effect on Substance Use: Comparisons Across Diverse Ethnic-Racial Youth

2019 ◽  
Author(s):  
Kevin Constante ◽  
Edward Huntley ◽  
Emma Schillinger ◽  
Christine Wagner ◽  
Daniel Keating
Keyword(s):  
Substance Use ◽  
Measurement Invariance ◽  
Latent Variables ◽  
Latent Variable ◽  
Path Model ◽  
Family Context ◽  
Partial Metric ◽  
Racial Groups ◽  
Protective Methods ◽  
Family Variables

Background: Although family behaviors are known to be important for buffering youth against substance use, research in this area often evaluates a particular type of family interaction and how it shapes adolescents’ behaviors, when it is likely that youth experience the co-occurrence of multiple types of family behaviors that may be protective. Methods: The current study (N = 1716, 10th and 12th graders, 55% female) examined associations between protective family context, a latent variable comprised of five different measures of family behaviors, and past 12 months substance use: alcohol, cigarettes, marijuana, and e-cigarettes. Results: A multi-group measurement invariance assessment supported protective family context as a coherent latent construct with partial (metric) measurement invariance among Black, Latinx, and White youth. A multi-group path model indicated that protective family context was significantly associated with less substance use for all youth, but of varying magnitudes across ethnic-racial groups. Conclusion: These results emphasize the importance of evaluating psychometric properties of family-relevant latent variables on the basis of group membership in order to draw appropriate inferences on how such family variables relate to substance use among diverse samples.

How do working memory, general anxiety and math anxiety affect female students’ math performance?

2020 ◽  
Author(s):  
Nachshon Korem ◽  
Orly Rubinsten
Keyword(s):  
Working Memory ◽  
Latent Variables ◽  
Math Anxiety ◽  
Verbal Working Memory ◽  
Math Performance ◽  
Equation Modeling ◽  
Current Evidence ◽  
Unique Contribution ◽  
Shared Variance ◽  
Numeric Information

Current evidence suggests that math anxiety and working memory govern math performance. However, these conclusions are largely based on simple correlations, without considering these variables as a network or examining correlations at the latent variables level. Thus, questions remain regarding the role of the unique and shared variance between math anxiety, working memory and math performance. The purpose of the current study was to (i) uncover the underlying relationships between the variables to understand the unique contribution of each element to the network; (ii) measure the shared variance and identify the interactions between affect and cognition that control math performance. Our analytical approach involved both network analysis approach and structural equation modeling, with a sample of 116 female students.Results show that math anxiety and working memory affect math performance by different mechanisms. Only working memory tests that included numeric information were correlated to math anxiety. Each of the various working memory tasks correlated differently to math performance: working memory as a single latent variable was a better predictor of math performance than visuospatial and verbal working memory as two separate latent variables. Overall, both working memory and math anxiety affect math performance. Working memory tasks that include numeric information can affect performance in math anxious individuals.

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