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<p>Moderation analyses allow a more nuanced understanding of the relationship between a predictor and an outcome. A limitation of traditional moderation analysis arises when addressing the hypothesis when using a moderator that does not account for unobserved heterogeneity in the population. This limitation can be addressed by extending moderation analyses to include a latent class analysis with auxiliary variables (as predictors and/or outcomes) where the moderator is the latent class variable. This tutorial specifies this extended moderation model with a latent class variable using the three-step manual approach (Asparouhov &amp; Muthén, <i>Structural Equation Modeling: A Multidisciplinary Journal</i>, <i>21</i>, 329-341, <CitationRef CitationID="CR1">2014</CitationRef>). Data from the Longitudinal Survey of American Life illustrates this approach within the context of science attitudes. Specifically, a latent class variable (science attitudes) is hypothesized to moderate the relationship between a predictor (science achievement) and an outcome (interest in science issues), while controlling for demographic variables.</p>

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Moderation with a latent class variable: A tutorial and example

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年4月10日

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  • Dina Ali Naji Arch,
  • Karen Nylund-Gibson,
  • Marsha Ing

摘要

Moderation analyses allow a more nuanced understanding of the relationship between a predictor and an outcome. A limitation of traditional moderation analysis arises when addressing the hypothesis when using a moderator that does not account for unobserved heterogeneity in the population. This limitation can be addressed by extending moderation analyses to include a latent class analysis with auxiliary variables (as predictors and/or outcomes) where the moderator is the latent class variable. This tutorial specifies this extended moderation model with a latent class variable using the three-step manual approach (Asparouhov & Muthén, Structural Equation Modeling: A Multidisciplinary Journal, 21, 329-341, 2014). Data from the Longitudinal Survey of American Life illustrates this approach within the context of science attitudes. Specifically, a latent class variable (science attitudes) is hypothesized to moderate the relationship between a predictor (science achievement) and an outcome (interest in science issues), while controlling for demographic variables.