Method Selection in Multiple Regression Analysis for Psychological Research
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Abstract
Multiple regression analysis is a crucial tool in psychological research. This article presents the method selection process for applying multiple regression by comparing various approaches, including Enter, Stepwise, Remove, Backward Elimination, and Forward Selection. Each method is evaluated based on criteria such as theoretical assumptions, model complexity, sample size, and research objectives. The advantages, disadvantages, and conditions for utilizing these methods are discussed in detail, along with examples from psychological research. This guidance aims to assist researchers in selecting the most appropriate analytical method to align with their research objectives, thereby enhancing the reliability and validity of regression analysis in behavioral studies.
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References
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