Code & Examples

The following page provides links to code, examples, and supplementary materials to papers and chapters on which I have worked. The code here may differ from the published versions, as this code will include any updates I have made. Please let me know if you find this code useful or have suggestions, corrections, or questions.

Stochastic differential equation (SDE) models are a promising method for modeling intraindividual change and variability. Applications of SDEs in the social sciences are relatively limited, as these models present conceptual and programming challenges. This article presents a novel method for conceptualizing SDEs. This method uses structural equation modeling (SEM) conventions to simplify SDE specification, the flexibility of SEM to expand the range of SDEs that can be fit, and SEM diagram conventions to facilitate the teaching of SDE concepts. This method is a variation of latent difference scores (McArdle, 2009; McArdle & Hamagami, 2001) and the oversampling approach (Singer, 2012), and approximates the advantages of analytic methods such as the exact discrete model (Oud & Jansen, 2000) while retaining the modeling fiexibility of methods such as latent differential equation modeling (Boker, Neale, & Rausch, 2004). A simulation and empirical example are presented to illustrate that this method can be implemented on current computing hardware, produces good approximations of analytic solutions, and can flexibly accommodate novel models.


No Need to be Discrete: A Method for Continuous Time Mediation Analysis (2015)

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Generalized Orthogonal Derivative Estimates (GOLD) (2010)

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Reservoir model (2013)

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The Oxford Handbook of Quantitative Methods, Vol. II. (2013)

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The Handbook of Research Methods for Studying Daily Life (2011)

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Observed and Expected Matrices (2010)

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Generalized Local Linear Approximation (GLLA) (2009)

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Smoothing–Independent Estimation of Oscillators (2009)

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