Background This study investigated whether the timing of birth of the younger siblings was associated with the risk of the older siblings’ developmental vulnerability in early childhood. Methods Linkage of population-level birth registration, hospital, and perinatal datasets to Australian Early Development Census (AEDC) records (2009–2015), enabled follow-up of a cohort of 32,324 Western Australia born singletons. Children with scores <10th percentile on an individual AEDC domain>(Physical Health and Wellbeing; Social Competence; Emotional Maturity; Language and Cognitive Skills (school-based); and Communication Skills and General Knowledge) were classified as developmentally vulnerable. Modified Poisson Regression was used to estimate relative risks (RR) for associations between post-birth interpregnancy intervals (IPIs) and developmental vulnerability. Results Relative to post-birth IPIs of 18–23 months, post-birth IPIs of <6 and>6–11 months were associated with a
We focus on regression models that consist of (i) a model for the conditional mean of the outcome and (ii) a distributional assumption about the distribution of the outcome, both conditional on the regressors. Generalised linear models form a well-known example. The choice of the outcome distribution is often motivated by prior or background knowledge of the researcher, or it is simply chosen for convenience. We propose smooth goodness of fit tests for testing the distributional assumption in regression models. The tests arise from embedding the regression model in a smooth family of alternatives, and constructing appropriate score tests that correctly account for nuisance parameter estimation. The tests are customised, focussed and comprehensive. We present several examples to illustrate the wide applicability of our method. A small simulation study demonstrates that our tests have power to detect important deviations from the hypothesised model.
2022 MAY 09 By a News Reporter-Staff News Editor at Insurance Daily News New study results on risk management have been published. Funders for this research include The Society of Actuaries’ Committee on Knowledge and Extension Research and the Casualty Actuarial Society Award: 2016.. Our news journalists obtained a quote from the research from University.