July 25, 2024Behavior Research MethodsOpen Access

Estimating nonlinear effects of random slopes: A comparison of multilevel structural equation modeling with a two-step, a single-indicator, and a plausible values approach

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Authors

SHSarah HumbergUniversity of Münster SGSimon GrundUniversität Hamburg SNSteffen NestlerUniversity of Münster

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Implication

Simulation study compares nonlinear random slope models for intrapersonal dynamics, demonstrating superior parameter accuracy for latent interactions over simplified approaches.

Key Points

Accurate parameter estimates for nonlinear effects of random slopes are achieved through multilevel structural equation modeling, avoiding single-indicator biases.
Simulation study evaluates three classes of nonlinear effects across parameter estimates, comparing latent interactions against a plausible values approach.
Supports practical implementation through code templates and illustrative examples, advancing the study of intrapersonal dynamics and within-person association patterns.

Cite This Study

Humberg et al. (2024) studied this question.

synapsesocial.com/papers/68e5f0b3b6db6435875859ba https://doi.org/10.3758/s13428-024-02462-9

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Implication

Simulation study compares nonlinear random slope models for intrapersonal dynamics, demonstrating superior parameter accuracy for latent interactions over simplified approaches.

Estimating nonlinear effects of random slopes: A comparison of multilevel structural equation modeling with a two-step, a single-indicator, and a plausible values approach

Discussion

Member takes

Implication

Key Points

Cite This Study

Estimating nonlinear effects of random slopes: A comparison of multilevel structural equation modeling with a two-step, a single-indicator, and a plausible values approach

Discussion

Member takes

Implication

Key Points

Cite This Study

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