Continuous treatments propensity scoring remains understudied as the majority of methods are focused on the binary treatment setting. Current propensity score methods for continuous treatments typically rely on weighting in order to produce causal estimates. It has been shown that in some continuous treatment settings, weighting methods can result in worse covariate balance than had no adjustments been made to the data. Furthermore, weighting is not always stable, and resultant estimates may be unreliable due to extreme weights. These issues motivate the current development of novel propensity score stratification techniques to be used with continuous treatments. Specifically, the generalized propensity score cumulative distribution function (GPS-CDF) and the nonparametric GPS-CDF approaches are introduced. Empirical CDFs are used to stratify subjects based on pretreatment confounders in order to produce causal estimates. A detailed simulation study shows superiority of these new stratification methods based on the empirical CDF, when compared with standard weighting techniques. The proposed methods are applied to the "Mexican-American Tobacco use in Children" study to determine the causal relationship between continuous exposure to smoking imagery in movies, and smoking behavior among Mexican-American adolescents. Linsitinib These promising results provide investigators with new options for implementing continuous treatment propensity scoring. This systematic review and meta-analysis compared previously documented inefficiencies in central coherence and set-shifting between people with nonunderweight eating disorders (bulimia nervosa and binge-eating disorder) and people with anorexia nervosa. We performed random-effects meta-analyses on 16 studies (1,112 participants) for central coherence and 38 studies (3,505 participants) for set-shifting. Random effects meta-regressions were used to test whether the effect sizes for people with nonunderweight eating disorders were significantly different from the effect sizes for people with anorexia nervosa. People with anorexia nervosa (Hedge's g = -0.53, 95% CIs -0.80, -0.27, p < .001) and bulimia nervosa (Hedge's g = -0.70, 95% CIs -1.14, -0.25, p = .002), but not binge-eating disorder, had significantly poorer central coherence than healthy controls. Similarly, people with anorexia nervosa (Hedge's g = -0.38, 95% CIs -0.50, -0.26, p < .001) and bulimia nervosa (Hedge's g = -0.55, 95% CIs -0.81orexia nervosa. Clinically, this suggests that people with bulimia nervosa might benefit from adjunctive approaches to address these inefficiencies, such as cognitive remediation therapy.In this paper it is shown that under the random effects generalized partial credit model for the measurement of a single latent variable by a set of polytomously scored items, the joint marginal probability distribution of the item scores has a closed-form expression in terms of item category location parameters, parameters that characterize the distribution of the latent variable in the subpopulation of examinees with a zero score on all items, and item-scaling parameters. Due to this closed-form expression, all parameters of the random effects generalized partial credit model can be estimated using marginal maximum likelihood estimation without assuming a particular distribution of the latent variable in the population of examinees and without using numerical integration. Also due to this closed-form expression, new special cases of the random effects generalized partial credit model can be identified. In addition to these new special cases, a slightly more general model than the random effects generalized partial credit model is presented. This slightly more general model is called the extended generalized partial credit model. Attention is paid to maximum likelihood estimation of the parameters of the extended generalized partial credit model and to assessing the goodness of fit of the model using generalized likelihood ratio tests. Attention is also paid to person parameter estimation under the random effects generalized partial credit model. It is shown that expected a posteriori estimates can be obtained for all possible score patterns. A simulation study is carried out to show the usefulness of the proposed models compared to the standard models that assume normality of the latent variable in the population of examinees. In an empirical example, some of the procedures proposed are demonstrated. Maternal hemorrhage protocols involve risk screening. These protocols prepare clinicians for potential hemorrhage and transfusion in individual patients. Patient-specific estimation and stratification of risk may improve maternal outcomes. Prediction models for hemorrhage and transfusion were trained and tested in a data set of 74 variables from 63 973 deliveries (97.6% of the source population of 65 560 deliveries included in a perinatal database from an academic urban delivery center) with sufficient data at pertinent time points antepartum, peripartum, and postpartum. Hemorrhage and transfusion were present in 6% and 1.6% of deliveries, respectively. Model performance was evaluated with the receiver operating characteristic (ROC), precision-recall curves, and the Hosmer-Lemeshow calibration statistic. For hemorrhage risk prediction, logistic regression model discrimination showed ROCs of 0.633, 0.643, and 0.661 for the antepartum, peripartum, and postpartum models, respectively. These improve upon thository, including a form allowing risk factor inputs and outputs of CMQCC risk, alongside our numerical risk estimation and stratification of hemorrhage and transfusion.Drought stress imposes a serious threat to crop productivity and nutritional security. Drought adaptation mechanisms involve complex regulatory network comprising of various sensory and signaling molecules. In this context, melatonin has emerged as a potential signaling molecule playing a crucial role in imparting stress tolerance in plants. Melatonin pretreatment regulates various plant physiological processes such as osmoregulation, germination, photosynthesis, senescence, primary/secondary metabolism, and hormonal cross-talk under water deficit conditions. Melatonin-mediated regulation of ascorbate-glutathione (AsA-GSH) cycle plays a crucial role to scavenge reactive oxygen species generated in the cells during drought. Here, in this review, the current knowledge on the role of melatonin to ameliorate adverse effects of drought by modulating morphological, physiological, and redox regulatory processes is discussed. The role of melatonin to improve water absorption capacity of roots by regulating aquaporin channels and hormonal cross-talk involved in drought stress mitigation are also discussed.