Expectations concerning future familial patterns among urban and kibbutz youth in Israel

"The purpose of this study was to compare the expectations and concepts urban and kibbutz adolescents [in Israel] have concerning their future families, and to compare the patterns desired by adolescents with the patterns existing in their parents' homes. The areas investigated included role allocation between husband and wife, and desired age [at] marriage and family size. The research population consisted of urban (174) and kibbutz (97) adolescents ages 17-18." "Overall..., concerning desired patterns of familial role allocation and marriage age, kibbutz and city adolescents show similar trends. However, concerning family size, differences still exist. Also, in both localities, there seem to exist differences between boys and girls concerning their future families."     

On some probability distributions for forward birth interval

Statisticians from Varanasi, India have proposed 2 mathematical models for forward birth interval which are more realistic than past models. For example, past models have assumed fecundability to be constant throughout a woman's reproductive life. On the other hand, the proposed models assume fecundability changes with parity. Further the statisticians use all types of marital durations making their models usable even for short marriage durations. The 1st model uses a parity specific model to develop a model for forward birth interval regarless of parity. The statisticians also include moments of the 1st and 2nd models as expressed for the rth order raw movement of these models to estimate some of their parameters. These models can be used to conduct prospective surveys of family planning programs since birth intervals can best evaluate the effect of these programs. These models have not yet been advanced enough to follow women over a fixed period, however. They only observe women until the last woman conceives. The statisticians do not apply the models to parity specific data because they were not available. Yet they do run the models with parities 0 and 1. The models reveal that the mean length of forward birth interval is strongly influenced by the conception rate which the woman has at the time of the survey. Thus, if women with a certain parity in a community begin an effective family planning method on the survey day, which in effect would reduce the prevailing conception rate, that method would significantly postpone the next live birth.     

Intergenerational Profiles of Socioeconomic (Dis)advantage and Obesity During the Transition to Adulthood

Investigations of socioeconomic status (SES) and health during the transition to adulthood in the United States are complicated by the later and more varied transitions in residence, employment, schooling, and social roles compared with previous generations. Parental SES is an important influence during adolescence but cannot sufficiently capture the SES of the independent young adult. Typical, single SES indicators based on income or education likely misclassify the SES of young adults who have not yet completed their education or other training, or who have entered the labor force early with ultimately lower status attainment. We use a latent class analysis (LCA) framework to characterize five intergenerational SES groups, combining multidimensional SES information from two time points—that is, adolescent (parental) and young adult (self) SES data. Associations of these groups with obesity, a high-risk health outcome in young adults, revealed nuanced relationships not seen using traditional intergenerational SES measures. In males, for example, a middle-class upbringing in adolescence and continued material advantage into adulthood was associated with nearly as high obesity as a working poor upbringing and early, detrimental transitions. This intergenerational typology of early SES exposure facilitates understanding of SES and health during young adulthood.     

Bayesian Representation of Stochastic Processes under Learning: de Finetti Revisited

A probability distribution governing the evolution of a stochastic process has infinitely many Bayesian representations of the form μ=∫μdλ(θ). Among these, a natural representation is one whose components ( μ's) are ‘learnable’ (one can approximate μ by conditioning μ on observation of the process) and ‘sufficient for prediction’ (μ's predictions are not aided by conditioning on observation of the process). We show the existence and uniqueness of such a representation under a suitable asymptotic mixing condition on the process. This representation can be obtained by conditioning on the tail-field of the process, and any learnable representation that is sufficient for prediction is asymptotically like the tail-field representation. This result is related to the celebrated de Finetti theorem, but with exchangeability weakened to an asymptotic mixing condition, and with his conclusion of a decomposition into i.i.d. component distributions weakened to components that are learnable and sufficient for prediction.     

Revising Infant Mortality Rates for the Early Twentieth Century United States

Accurate vital statistics are required to understand the evolution of racial disparities in infant health and the causes of rapid secular decline in infant mortality during the early twentieth century. Unfortunately, U.S. infant mortality rates prior to 1950 suffer from an upward bias stemming from a severe underregistration of births. At one extreme, African American births in southern states went unregistered at the rate of 15 % to 25 %. In this study, we construct improved estimates of births and infant mortality in the United States for 1915–1940 using recently released complete count decennial census microdata combined with the counts of infant deaths from published sources. We check the veracity of our estimates with a major birth registration study completed in conjunction with the 1940 decennial census and find that the largest adjustments occur in states with less-complete birth registration systems. An additional advantage of our census-based estimation method is the extension backward of the birth and infant mortality series for years prior to published estimates of registered births, enabling previously impossible comparisons and estimations. Finally, we show that underregistration can bias effect estimates even in a panel setting with specifications that include location fixed effects and place-specific linear time trends.