The results of this study are most compatible with no association between maternal use of SSRIs in early pregnancy and cardiac malformations or septal defects in the offspring. Published 2013. This article is a U.S. Government work and is in the public domain in the USA.

Clinical Practice Research Datalink Read codes for CCMs have 93% PPV and most likely point to true cases. However, the accuracy of diagnosis dates and the age at diagnosis may not be as reliable. The findings of this study indicate that GPs use information beyond what is available for researchers in the EMR to confirm clinical diagnoses when responding to validation questionnaires. Published 2013. This article is a U.S. Government work and is in the public domain in the USA.

Piecewise latent growth models (LGMs) for linear-linear processes have been well-documented and studied in recent years. However, in the latent growth modeling literature, advancements to other functional forms as well as to multiple changepoints or knots have been nearly non-existent. This manuscript deals with three extensions. The first is to a piecewise latent growth model incorporating higher-order polynomials. The second is to extend the basic framework to three phases. The last extension is to inherently nonlinear functions. In these extensions, the changepoint(s) is a parameter to be estimated and may be fixed or allowed to vary across subjects as an application warrants. The approaches are developed and two illustrative empirical examples from psychology are used to highlight the methodological nuances. Annotated statistical software is provided to make these elaborations accessible to practitioners and methodologists.Change that occurs in distinct phases or regimes can be modeled using piecewise (spline) functions (see, e.g., Gallant & Fuller, 1973; Seber & Wild, 1989, Chapter 9) where the overall piecewise regression model is a complex amalgamation of submodels, each of which is associated with a distinct interval of time (see, e.g., Cudeck & Klebe, 2002). Because the functional form in each segment can be tailored to fit the localized data (Cudeck & Harring, 2010), the piecewise growth model is quite flexible and can accommodate a variety of modeling scenarios that are not adequately captured by mathematical functions for singlestage change processes (Grimm et al., 2011;Sterba, 2014) and/or often yield parameters with more meaningful and substantive interpretations.For example, consider the two-phase linear-linear piecewise model depicted in Fig. 1. The changepoint distinguishes between two phases comprising the overall change process. On the left-hand side of the changepoint are the