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Titlebook: Dependent Data in Social Sciences Research; Forms, Issues, and M Mark Stemmler,Wolfgang Wiedermann,Francis L. Huang Book 2024Latest edition

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楼主: irritants
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Jaitri Das,Buddhadeb Chattopadhyayn models for longitudinal data, focusing on continuous-time (CT) models. Unlike the more widely used discrete-time (DT) models, CT models do not require the time intervals between measurements to be equal and, therefore, can adapt effortlessly to irregular sampling schemes. Thus, our resulting appro
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Mauro Ferrario,Maria Clelia Righiearly related to each other, and errors may be multiplicative. Thus, the present chapter discusses linearizable non-linear models for which distributional and independence-based direction dependence measures are applicable. Simulation results suggest that direction of dependence properties of linear
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Engineered Fe-Based Nanocolumnar Films,n the construction of analytical models. In this chapter, we look at how longitudinal data are analyzed in latent growth curve models. We focus on the real-world problem of sampling-time variation, when individuals do not have exactly equal intervals between measurements, its consequences, and how t
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