Nonparametric estimation of the conditional distribution function in a semiparametric censorship model

In this paper we propose a new nonparametric estimator of the conditional distribution function under a semiparametric censorship model. We establish an asymptotic representation of the estimator as a sum of iid random variables, balanced by some kernel weights. This representation is used for obtaining large sample results such as the rate of uniform convergence of the estimator, or its limit distributional law. We prove that the new estimator outperforms the conditional Kaplan–Meier estimator for censored data, in the sense that it exhibits lower asymptotic variance. Illustration through real data analysis is provided.     

A note on bias reduction of maximum likelihood estimates for the scalar skew t distribution

The skew t distribution is a flexible parametric family to fit data, because it includes parameters that let us regulate skewness and kurtosis. A problem with this distribution is that, for moderate sample sizes, the maximum likelihood estimator of the shape parameter is infinite with positive probability. In order to try to solve this problem, Sartori (2006) has proposed using a modified score function as an estimating equation for the shape parameter. In this note we prove that the resulting modified maximum likelihood estimator is always finite, considering the degrees of freedom as known and greater than or equal to 2.     

Inflation projections for monetary policy decision making

Many central banks set inflation targets over the medium term and inflation projections are a key input for monetary policy decision making. In this paper, we present the procedures used by the Spanish Central Bank staff to project consumer price inflation. We also provide some illustrations of their policy uses, such as fan charts, deflation probabilities and the monitoring of inflation targets.     

Relationship between duration of second stage of labour and postpartum anaemia

Aim

To assess the relationship between the duration of the second stage of labour and postpartum anaemia during vaginal birth.

Exploring the relationship between parents’ and children’s housework time in Spain

Intergenerational transmission has been successfully employed in economic research to explain the persistence of certain economic behaviors across generations. This paper evaluates the relevance of this transmission process in the formation of gender roles during childhood. In particular, we analyze the relationship between parents?? and children??s housework allocation patterns. We propose a simple theoretical model that predicts that parents with a strong adherence to gender to traditional gender norms??as proxied by their division of household labor??are more likely to allocate housework to children in a way that reflects stereotypes of men??s and women??s domestic tasks. The empirical application is carried out with data from the 2002?C2003 Spanish Time Use Survey. The sample restricts to two-parent households with at least one child aged 10?C17?years. We find a significant positive correlation between a more egalitarian parents?? allocation of housework and a less asymmetrical distribution of domestic chores between sons and daughters.     

A simulation study of the Bennett test and Miller test for coefficients of variation

In the article, properties of the Bennett test and Miller test are analyzed. Assuming that the sample size is the same for each sample and considering the null hypothesis that the coefficients of variation for k populations are equal against the hypothesis that k ? 1 coefficients of variation are the same but differ from the coefficient of variation for the kth population, the empirical significance level and the power of the test are studied. Moreover, the dependence of the test statistic and the power of the test on the ratio of coefficients of variation are considered. The analyses are performed on simulated data.     

The Jackknife estimate of covariance of two Kaplan–Meier integrals with covariables

In this paper the Jackknife estimate of covariance of two Kaplan–Meier integrals with covariates is introduced. Its strong consistency is established under mild conditions. Several applications of the estimator are discussed.     

Expanded renal transplantation: a competing risk model approach

Multi-state models (MSMs) are useful to analyze survival data when, besides the event of main interest, one or more intermediate states of the individual are identified. These models take the several existing states and the possible transitions among them into account. At the same time, covariate effects on each transition intensity may be investigated separately and, therefore, MSMs are more flexible than the standard Cox proportional hazards model. In this work, we use MSMs to investigate the impact of the quality of a transplanted kidney for a group of patients at the Hospital Universitario Central de Asturias. Specifically, we use an illness-death model to study the evolution of patients with kidney disease who received a renal transplant after a dialysis period. The intermediate state is defined as the failure of the received organ, while the terminating state is the death of the patient. In order to increase the potential number of organs available for transplant, the standards of quality for the transplanted kidneys were relaxed (the new criteria are labeled expanded criteria), and these ‘expanded kidneys’ were transplanted in appropriate candidates (older patients, with higher prevalence of diabetes mellitus). Results suggest that the expanded kidneys have a minor effect on survival, while both the kidney mortality and the risk of death increase with the patient's age and the serum creatinine and serum hemoglobin levels.     

Strong consistency of presmoothed Kaplan–Meier integrals when covariables are present

It is known that the Kaplan–Meier estimation may be improved via presmoothing methods. In this article, we introduce an extended presmoothed Kaplan–Meier estimator in the presence of covariates. The main result is the strong consistency of general empirical integrals based on such an estimator. As applications, one can obtain a consis-tent multivariate empirical distribution under censoring, and also can obtain a consistent estimation of regression parameters. We illustrate the new estimation methods through simulations and real data analysis.     

Patterns of individual change and program satisfaction in a positive parenting program for parents at psychosocial risk

Despite the evidence of effectiveness of positive parenting programs, little is known about the typology of changes that parents at psychosocial risk undergo after an intervention. We compared individual patterns of change in three parenting outcomes in 256 at risk parents with young children attending the group‐based Growing Up Happily in the Family program delivered in municipal social services. We identified four clusters of individual change: Cluster 1 (30.6%) had negative changes in parental child‐rearing attitudes and parenting stress, Cluster 2 (27.7%) had positive changes in child‐rearing attitudes and negative results in parental perceived competence, and Cluster 3 (24.1%) and Cluster 4 (17.6%) showed overall better results. Residential area, type of social support, and quality of implementation characterized cluster membership. Participants in clusters with better results were more satisfied with the program than those with worse results. Practical recommendations are provided for the successful implementation of group parenting programs in family preservation services.