Family transitions in Young Adulthood

Using the first (1995) and third (2001-2002) waves of the Add Health survey, we examine women 's family transitions up to age 24. Only a third of all women marry, and a fifth of those marriages dissolve before age 24. Three out of eight women have afirst birth, with a substantial majority of those births outside of marriage: 66% for whites, 96% for blacks, and 72% for Mexican Americans. Cohabitation is the predominant union form; 59% of women cohabit at least once by age 24. Most cohabitations are short lived, with approximately one in five resulting in a marriage. We summarize the family and relationship experience of women up to age 24 in terms offour categories, each accounting for roughly a quarter of all women. Category 1 has the women who remain single nonparents. Category 2 has the early marriers, women whose marriage is not preceded by a first birth. Category 3 has those who become single parents. Category 4 has the women who cohabit at least once, but who do not marry or have a birth by age 24. The strictly ordered transitions of the 1950s are long gone and have been replaced by a variety of paths to adulthood.     

Zero variance Markov chain Monte Carlo for Bayesian estimators

Interest is in evaluating, by Markov chain Monte Carlo (MCMC) simulation, the expected value of a function with respect to a, possibly unnormalized, probability distribution. A general purpose variance reduction technique for the MCMC estimator, based on the zero-variance principle introduced in the physics literature, is proposed. Conditions for asymptotic unbiasedness of the zero-variance estimator are derived. A central limit theorem is also proved under regularity conditions. The potential of the idea is illustrated with real applications to probit, logit and GARCH Bayesian models. For all these models, a central limit theorem and unbiasedness for the zero-variance estimator are proved (see the supplementary material available on-line).     

General treatment of goodness-of-fit tests based on Kullback–Leibler information

This paper introduces a general goodness-of-fit test based on the estimated Kullback–Leibler information. The test uses the Vasicek entropy estimate. Two special cases of the test for location–scale and shape families are discussed. The results are used to introduce goodness-of-fit tests for the uniform, Laplace, Weibull and beta distributions. The critical values and powers for some alternatives are obtained by simulation.     

ML and Bayes estimation in a two-phase tandem queue with a second optional service and random feedback

ABSTRACT

In this article, we consider a two-phase tandem queueing model with a second optional service and random feedback. The first phase of service is essential for all customers and after the completion of the first phase of service, any customer receives the second phase of service with probability α, feedback to the tail of the first queue with probability β if the service is not successful and leaves the system with probability 1 ? α ? β. In this model, our main purpose is to estimate the parameters of the model, traffic intensity, and mean system size, in the steady state, via maximum likelihood and Bayesian methods. Furthermore, we find asymptotic confidence intervals for mean system size. Finally, by a simulation study, we compute the confidence levels and mean length for asymptotic confidence intervals of mean system size with a nominal level 0.95.     

Testing Normality Using Transformed Data

In this article, we first present a characterization of the normal distribution and then we introduce an exact goodness of fit test for normal distribution. The power of the proposed test under various alternatives is compared with the existing tests, by simulation.     

Testing the equality of matrix distributions

Statistical Methods & Applications - While matrices are usually used as the basic data structure for experiments with repeated measurements or longitudinal data, testing methods for the...     

A flexible generalization of the skew normal distribution based on a weighted normal distribution

The skew normal distribution of Azzalini (Scand J Stat 12:171–178, 1985) has been found suitable for unimodal density but with some skewness present. Through this article, we introduce a flexible extension of the Azzalini (Scand J Stat 12:171–178, 1985) skew normal distribution based on a symmetric component normal distribution (Gui et al. in J Stat Theory Appl 12(1):55–66, 2013). The proposed model can efficiently capture the bimodality, skewness and kurtosis criteria and heavy-tail property. The paper presents various basic properties of this family of distributions and provides two stochastic representations which are useful for obtaining theoretical properties and to simulate from the distribution. Further, maximum likelihood estimation of the parameters is studied numerically by simulation and the distribution is investigated by carrying out comparative fitting of three real datasets.     

On comparing,classifying and clustering several dependent regression models

Classifying several regression models fitted on a dataset is one of the most problems in data analysis. In other words, scientists are interested in comparing several regression models that can be used for a dataset. In this paper, an approach will be used to compare and classify several dependent regression models. Then the performance of the proposed method is investigated using simulation study and real example.     

Social Background Differences in Early Family Behavior

Social background has historically been recognized as a major factor influencing family behavior, though recent work has largely emphasized racial/ethnic influences. Here we use 1994 – 1995 and 2001 – 2002 Add Health data to examine the cohabitation, first marriage, and first birth experience of young women. In a multistate life table context, hypothetical cohorts specified in terms of race and mother’s education are followed, from age 11 to age 24, as they move through 6 family‐related statuses. The results indicate that, for both Black and White women, a higher level of maternal education is generally associated with less cohabitation, less marriage, fewer first births, and a higher percentage of women who experience none of those transitions before age 24. Racial and social background differences are conceptually and empirically distinct. Because mother’s education is associated with substantially different trajectories of early family behavior for both Blacks and Whites, we argue that social background merits increased attention in research on contemporary American family patterns.     

Professors,Ideology and Housework

This paper presents, for the first time, multivariate analyses of Canadian national data and tests the relationship between class-based egalitarianism and housework for married and cohabiting male and female university professors in 2000. Consistent with evidence in the general population, gender accounts for more variation in housework than a host of other predictors (i.e., class- and gender-based ideology, institutional contexts and resources, available time, presence of children, age, minority racial status, and religiosity). Nevertheless, these forces play important roles in increasing or decreasing domestic labor contributions of both male and female academics. Among these, professors who possess class-based egalitarian views do more housework, and egalitarianism increases domestic labor contributions of males and decreases that of females.