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<!DOCTYPE html>
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<head>
<title>dynrR</title>
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<ul class="navbar-nav ml-auto">
<li class="nav-item"><a href="index.html" class="nav-link">Home</a></li>
<li class="nav-item"><a href="about.html" class="nav-link">References</a></li>
<li class="nav-item"><a href="FAQ.html" class="nav-link">FAQ</a></li>
<li class="nav-item"><a href="index.html#contact" class="nav-link">Contact</a></li>
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<h1 class="mb-2 bread">Publications</h1>
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<h2 class="mb-3" style="text-align:center">Want to learn more about dynr? </h2>
<h3 style="text-align:left"> Please check out some of our publications introducing current and new features of dynr, and applications utilizing dynr.</h3>
<img src="images/freddy-castro-u3ajSXhZM_U-unsplash.jpg" width=1000px, height=450px;>
</p>Photo by <a href="https://unsplash.com/@readysetfreddy?utm_source=unsplash&utm_medium=referral&utm_content=creditCopyText">Freddy Castro</a> on <a href="https://unsplash.com/s/photos/journal?utm_source=unsplash&utm_medium=referral&utm_content=creditCopyText">Unsplash</a></p>
<h3> Current and New Features of dynr</h3>
<ol type="1">
<li>You, D-J., Hunter, M. D., Chen, M., & Chow, S-M. (2020). <a href="https://pubmed.ncbi.nlm.nih.gov/31264463/">A diagnostic procedure for detecting model misspecification in linear state–space.</a> <em>Multivariate Behavioral Research</em>, 55(2), 231-255. DOI:
10.1080/00273171.2019.1627659.</li>
<li>Ou, L., Hunter, M. D., & Chow, S-M. (2019). <a href="https://journal.r-project.org/archive/2019/RJ-2019-012/index.html">What’s for dynr: A package for linear and nonlinear dynamic modeling in R.</a> <em>The R Journal</em>; DOI: 10.32614/RJ-2019-012.</li>
<li>Li, Y., Ji, L., Oravecz, Z., Brick, Timothy R., Hunter, M. D., & Chow, S-M. (2019).
dynr.mi: <a href="http://waset.org/Publications?p=149,
eISSN:1307-6892">An R Program for Multiple Imputation in Dynamic Modeling.</a>
<em>International Journal of Computer, Electrical, Automation, Control and
Information Engineering </em>, 13(5), 302-311. World Academy of Science, Engineering and Technology,
International Science Index 149, 2019.</li>
</ol>
<h3> Applications Utilizing dynr</h3>
<ol type="1">
<li>Chen, M., Chow, S-M., Hammal, Z., Cohn, J. & Messinger, D. (in press). A
<a href="https://www.researchgate.net/publication/342142636_A_Person-_and_Time-Varying_Vector_Autoregressive_Model_to_Capture_Interactive_Infant-Mother_Head_Movement_Dynamics">Person- and time-varying vector autoregressive model to capture interactive
infant-mother head movement dynamics.</a> <em>Multivariate Behavioral Research.</em> DOI:
10.1080/00273171.2020.1762065</li>
<li>Chow, S-M., You, D-J., & *Clouthier, T. (in press). A regime-switching framework for
formulating multi-phase linear and nonlinear growth curves. In (Eds.). MARCES Series: Innovative Psychometric Modeling and Methods. Charlotte, NC: Information Age Publishing, Inc.</li>
<li> Chow, S-M. (2019). <a href="https://www.nihms.nih.gov/pmc/articlerender.fcgi?artid=1520409">Practical Tools and Guidelines for Exploring and Fitting Linear and Nonlinear Dynamical Systems Models.</a> <em>Multivariate Behavioral Research</em>, 54(5), 690-718. </li>
<li>Chen, M., Chow, S-M., & Hunter, M. D. (2018). Stochastic differential equation
models with time-varying parameters. In K. van Montford, H. Oud, & M. Voelkle (Eds.). Continuous-Time Modeling in the Behavioral and Related Sciences (pp. 205-238). Cham: Springer International publishing. Doi: 10.1007/978-3-319-77219-6_9</li>
<li>Ji, L., & Chow, S-M. (2018). Methodological Issues and Extensions to the Latent
Difference Score Framework. In Ferrer, M., Grimm, K., & Boker, S.M. (Eds.). Longitudinal Multivariate Psychology, Multivariate Applications Series (pp. 9-37). New York, NY: Taylor & Francis. Doi: 10.4324/9781315160542-2.</li>
<li>Chow, S.-M., Ou. L, Ciptadi, A., Prince, E., You, D., Hunter, M. D., Rehg, J. M.,
Rozga, A., & Messinger, D. S. (2018). <a href="https://pubmed.ncbi.nlm.nih.gov/29557080/">Differential equation modeling
approaches to representing sudden shifts in intensive dyadic interaction data.</a> <em>Psychometrika</em>, 83(2):476-510. doi: 10.1007/s11336-018-9605-1.</li>
</ol>
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