scholarly journals Analyzing factorial survey data with structural equation models

2021 ◽  
pp. 004912412110431
Author(s):  
Bert Weijters ◽  
Eldad Davidov ◽  
Hans Baumgartner

In factorial survey designs, respondents evaluate multiple short descriptions of social objects (vignettes) that experimentally vary different levels of attributes of interest. Analytical methods (including individual-level regression analysis and multilevel models) estimate the weights (or utilities) assigned to the levels of the different attributes by participants to arrive at an overall response to the vignettes. In the current paper, we explain how data from factorial surveys can be analyzed in a structural equation modeling framework using an approach called structural equation modeling for within-subject experiments. We review the use of factorial surveys in social science research, discuss typically used methods to analyze factorial survey data, introduce the structural equation modeling for within-subject experiments approach, and present an empirical illustration of the proposed method. We conclude by describing several extensions, providing some practical recommendations, and discussing potential limitations.

2020 ◽  
Vol 17 (06) ◽  
pp. 2050040
Author(s):  
Alejandro Coronado-Medina ◽  
Jose Arias-Pérez ◽  
Geovanny Perdomo-Charry

This paper analyzes the mediating effect of absorptive capacity (AC) on the relationship between digital transformation from e-business capabilities (EBC) perspective and product innovation (PI). Structural equation modeling (SEM) was carried out with the survey data from a sample of firms that belong mainly to highly digitalized sectors. The results indicate the existence of a full mediation, which means knowledge derived from the digital operation of the business can only result in PI if AC plays an intermediation role. Hence, this finding calls into question the idea that digitalization alone and automatically acts as a PI driver.


2018 ◽  
Vol 24 (3) ◽  
pp. 354
Author(s):  
Diki Ferdiana ◽  
Ayu Chairina Laksmi

ABSTRACT This study examinedthe influence of the process of reporting and depositing taxes as well as satisfaction and compliance in personal taxpayers in Sleman regency against economic resilience. The purpose of this study was to analyzed the influence of the process of reporting and depositing taxes and taxpayer compliance and compliance with economic resilience.This research was an empirical research by taking samples of taxpayers in Sleman District. Survey data were analyzed statistically using descriptive method and Structural Equation Modeling (SEM) with the help of computer program AMOS v22. The results showed that the process of reporting and depositing taxes and satisfaction and compliance in taxpayershad posistive influence, which had a significant impact on the economic resilience of the region. This could be said as a form of economic resilience of the region which was the basis of national resilienceABSTRAK Penelitian ini mengkaji tentang pengaruh proses pelaporan dan penyetoran pajak serta kepuasan dan kepatuhan dalam wajib pajak pribadi di Kabupaten Sleman terhadap ketahanan ekonomi. Tujuan penelitian ini untuk menganalisis pengaruh proses pelaporan dan penyetoran pajak serta kepuasan dan kepatuhan wajib pajak terhadap ketahanan ekonomi.Penelitian ini merupakan penelitian empiris dengan mengambil sampel para wajib pajak di Kabupaten Sleman. Data survei dianalisis secara statistik menggunakan metode deskriptif dan Structural Equation Modeling (SEM) dengan bantuan program komputer AMOS v22.Hasil penelitian menunjukkan bahwa proses pelaporan dan penyetoran pajak serta kepuasan dan kepatuhan dalam wajib pajak berpengaruh posistif, yang berdampak signifikan terhadap ketahanan ekonomi wilayah. Hal ini dapat dikatakan sebagai wujud dari ketahanan ekonomi wilayah yang merupakan dasar dari ketahanan nasional. 


One Ecosystem ◽  
2020 ◽  
Vol 5 ◽  
Author(s):  
James Grace

It is possible that model selection has been the most researched and most discussed topic in the history of both statistics and structural equation modeling (SEM). The reason for this is because selecting one model for interpretive use from amongst many possible models is both essential and difficult. The published protocols and advice for model evaluation and selection in SEM studies are complex and difficult to integrate with current approaches used in biology. Opposition to the use of p-values and decision thresholds has been voiced by the statistics community, yet certain phases of model evaluation have been historically tied to reliance on p-values. In this paper, I outline an approach to model evaluation, comparison and selection based on a weight-of-evidence paradigm. The details and proposed sequence of steps are illustrated using a real-world example. At the end of the paper, I briefly discuss the current state of knowledge and a possible direction for future studies.


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