In this paper, a stochastic individual data model is considered. It accommodates occurrence times, reporting, and settlement delays and severity of every individual claims. This formulation gives rise to a model for the corresponding aggregate data under which classical chain ladder and Bornhuetter...
Polysubstance Exposure To assess the association of aggregate polysubstance exposure with ADHD risk, we computed a prenatal polysubstance exposure score in 4 ways to better describe estimated synergistic statistical effects between substances. First, using dichotomous yes vs no variables for each exposure...
O'Laughlin and Malle [137] further investigated people's perception of group vs. individual behaviour, focusing on intentionality of explanation. They investigated the relative agency of groups that consist of ‘unrelated’ individuals acting independently (aggregate groups) compared to groups acting toge...
These models are fit individually for each participant and each block to mitigate challenges interpreting fits to aggregate data (Ashby et al., 1994, Estes, 1956, Estes and Maddox, 2005). Consistent with prior research, we specified three classes of models, with multiple instantiations possible ...
16 Meta-analyses using individual participant data (IPD) estimate aggregate effect sizes using IPD from RCTs. The IPD maximize power to detect a true effect while allowing the exploration of study variability (eg, level of support, treatment adherence, setting) and participant characteristics as...
Clinical data indicate that men and women exhibit sex differences in the neuropathological and symptomatic progression of AD [7]. The lifetime risk for developing AD for 65-year-old females is twice that of men of the same age (12% vs. 6.3%, respectively) [8]. Furthermore, women show...
while EV managed charging program managers may turn elsewhere. Here, program managers could miss the opportunity to combine efforts and cut costs by employing a Grid-Edge DERMS solution that can aggregate devices ofanytype. In doing so, utilities can streamline their internal budgets, cutting devel...
Pair-wise connectivity between ROIs in the brain is estimated using atlases that aggregate together voxels based on some similarity measure. We use three different ROI sets (see Supplementary Tables 2–4). Data-driven ROI intersection set (INTR) Using the intersection volume created using the conju...
We assessed heterogeneity by estimating prediction intervals for all pairwise meta-analyses, and via the estimated values of τ for aggregate data NMAs (AD-NMA). We checked inconsistency in the networks using a local approach (back-calculation)25 as well as a global test (design-by-treatment)...
21,22 The random forest algorithm trains many decision-tree classifiers on bootstrapped samples of the data set using a random selection of features for each tree and then aggregates all the predictions from each tree into a final predicted probability.19 Model tuning was implemented using the ...