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Patterns of vulnerability in pregnancy and early childhood: Measurement, interactions, effect moderation and random coefficients in latent variable models

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If you have a question about this talk, please contact Michael Sweeting .

As yet models for developmental data rarely do justice to the complexity of measurement and process. We examine models for inferring abnormality within a context of developmental delay and for characterising the effects of pre-natal programming. In the first we use the SNAP and MLS studies of autism and specific language impairment to highlight the complex censoring that occurs when we attempt to use “regression” in language as an indicator of neurodevelopmental abnormality and the counter-intuitive associations to which it gives rise. In the second we explore foetal programming of markers of emotional regulation and the potential compensatory effects of early parenting. We estimate a model using gllamm in which a maternal behaviour latent variable derived from 4 ordinal items by an Item-Response Theory measurement model, moderates the impact of both maternal depression at 32-weeks of pregnancy and poor intra-uterine growth, on 6-month infant vagal tone and on vagal withdrawal in response to a social stressor.

GLLAMM – Generalized Linear Latent and Mixed Model

This talk is part of the MRC Biostatistics Unit Seminars series.

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MR3, Centre for Mathematical Sciences, Wilberforce Road, Cambridge Sackler Lecture Theare, Institute of Astronomy Webinar & LT2, Computer Laboratory, William Gates Building.

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