Eisert, Brady Christopher2024-04-112024-04-112024https://hdl.handle.net/2097/44226This report translates statistical research on congruence modeling to family science. In particular, it highlights the limitations of the latent congruence model (LCM; Cheung, 2009), which was recently re-branded as the dyadic score model (Iida et al., 2018). A general model for congruence research based on polynomial response surface analysis is presented, along with unconstrained and constrained examples of first- (linear), second- (quadratic), and third-order (cubic) polynomial models. Following Edwards’ (2009) critique, the LCM coefficients are shown to be equivalent to compound coefficients of the linear polynomial model that conceal the effects of its components. The implicit constraints and limitations of the LCM are demonstrated using an exploratory empirical example of sexual desire discrepancy’s effects on sexual satisfaction for heterosexual couple therapy clients. These results are discussed, followed by key takeaways for family scientists.en-US© the author. This Item is protected by copyright and/or related rights. You are free to use this Item in any way that is permitted by the copyright and related rights legislation that applies to your use. For other uses you need to obtain permission from the rights-holder(s).http://rightsstatements.org/vocab/InC/1.0/Latent congruence modelingResponse surface analysisPolynomial regressionWhat’s the difference? A clarification of the statistical assumptions in congruence modelingReport