1,720,988 research outputs found
Life course determinants of poor psychosocial health in adulthood: young motherhood as a mediating pathway
No full textBayesian spatial analysis of demographic survey data: An application to contraceptive use at first sexual intercourse
No full textIn this paper we analyze the spatial patterns of the risk of unprotected sexual intercourse for Italian women during their initial experience with sexual intercourse. We rely on geo-referenced survey data from the Italian Fertility and Family Survey, and we use a Bayesian approach relying on weakly informative prior distributions. Our analyses are based on a logistic regression model with a multilevel structure. The spatial pattern uses an intrinsic Gaussian conditional autoregressive (CAR) error component. The complexity of such a model is best handled within a Bayesian framework, and statistical inference is carried out using Markov Chain Monte Carlo simulation. In contrast with previous analyses based on multilevel model, our approach avoids the restrictive assumption of independence between area effects. This model allows us to borrow strength from neighbors in order to obtain estimates for areas that may, on their own, have inadequate sample sizes. We show that substantial geographical variation exists within Italy (Southern Italy has higher risks of unprotected first-time sexual intercourse). The findings are robust with respect to the specification of the prior distribution. We argue that spatial analysis can give useful insights on unmet reproductive health needs
Age at first sexual intercourse in Italy: A geographical approach
No full textUsing data from the "Survey on Sexual Behaviour of Italian Students - USS", we investigate the behaviour of Italian students at first sexual intercourse, focusing, in particular, on geographical patterns and employing event-history models. For both genders, we found significant spatial differentials. The geography of women's attitude towards their first sexual intercourse does not seem to be affected by their social and cultural background; this however is not the case for men, for whom the geographical dynamics are explained by background characteristics. Finally, we present a comparison between the results found in the above data set and the Italian Fertility Family Survey (FFS) andfind striking similarities between the two
L’allargamento dell’Unione Europea: una prospettiva demografica
No full textStudio della convergenza dei comportamenti demografici nell'Unione Europe
A multilevel extension of a Heckman-type model for longitudinal quality of life data subject to drop out in a multi-centre clinical trial
No full textAssessing the use of sample selection models in the estimation of fertility postponement effects
No full textSeveral studies have shown that at the individual level there exists a negative relationship between age at first birth and completed fertility. Using twin data in order to control for unobserved heterogeneity as possible source of bias, Kohler et al. (2001) showed the significant presence of such "postponement effect" at the micro level. In this paper, we apply sample selection models, where selection is based on having or not having had a first birth at all, to estimate the impact of postponing first births on subsequent fertility for four European nations, three of which have now lowest-low fertility levels. We use data from a set of comparative surveys (Fertility and Family Surveys), and we apply sample selection models on the logarithm of total fertility and on the progression to the second birth. Our results show that postponement effects are only very slightly affected by sample selection biases, so that sample selection models do not improve significantly the results of standard regression techniques on selected samples. Our results confirm that the postponement effect is higher in countries with lowest-low fertility levels
Nonparametric estimation methods for sparse contingency tables
No full textThe problems related with multinomial sparse data analysis have been widely underlined in statistical literature in recent years. Concerning the estimation of the mass distribution, it has been widely spread the usage of nonparametric methods, particularly in the framework of ordinal variables. The aim of this paper is to evaluate the performance of kernel estimators in the framework of sparse contingency tables with ordinal variables comparing them with alternative methodologies. Moreover, an approach to estimate the mass distribution nominal variables based on a kernel estimator is proposed. At the end a case study in actuarial field is presented
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