1. What contributions have the authors mentioned in the paper "Analyzing policy capturing data using structural equation modeling for within-subject experiments (semwise)" ?
The authors present the SEMWISE ( Structural Equation Modeling for Within-Subject Experiments ) approach for analyzing policy capturing data.. The authors describe the core SEMWISE model and propose several extensions ( how to incorporate non-binary attributes and interactions ; how to model multiple indicators of the response variable ; how to relate the latent weight factors to antecedents and/or consequences ; and how to simultaneously investigate several populations of respondents ).. The authors illustrate the approach with two empirical examples, compare and contrast the SEMWISE approach with multi-level modeling ( MLM ), discuss how researchers can choose between SEMWISE and MLM, and provide implementation guidelines.
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2. What future works have the authors mentioned in the paper "Analyzing policy capturing data using structural equation modeling for within-subject experiments (semwise)" ?
Future research may want to explore which types of formats perform best in terms of respondent motivation and data quality.. In certain types of policy capturing studies, researchers who plan to use SEMWISE may deem it beneficial to limit the number of profiles presented to respondents to reduce respondent burden and leave more opportunity for measuring other variables, specifically SEMWISE 29 when the goal is to study a broader nomological network surrounding the weight factors.. Future research needs to investigate to what extent such problems occur and how they can be resolved.. Second, on a more pragmatic level, data management, data analysis, and interpretation of the results in a SEMWISE framework may be nonstandard and initially challenging, especially for non-SEM users.
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