Data skeletons: simultaneous estimation of multiple quantiles for massive streaming datasets with applications to density estimation

We consider the problem of density estimation when the data is in the form of a continuous stream with no fixed length. In this setting, implementations of the usual methods of density estimation such as kernel density estimation are problematic. We propose a method of density estimation for massive datasets that is based upon taking the derivative of a smooth curve that has been fit through a set of quantile estimates. To achieve this, a low-storage, single-pass, sequential method is proposed for simultaneous estimation of multiple quantiles for massive datasets that form the basis of this method of density estimation. For comparison, we also consider a sequential kernel density estimator. The proposed methods are shown through simulation study to perform well and to have several distinct advantages over existing methods.     

Couple Attitudes and Agreement Regarding Pregnancy Wantedness in the Philippines

We compare husbands' and wives' views of the wantedness of their most recent pregnancy in the Philippines, a country where relatively high levels of unintended fertility persist. This research is an extension of earlier work that looked separately at individual men's and women's responses. We analyze survey data for 369 couples and find that those most at risk of experiencing a pregnancy that neither spouse wanted tended to be higher parity couples, those who were more fatalistic, those who were practicing Catholics who attended religious services frequently, and those among whom the husband was the sole breadwinner. Higher parity women and older women were also more apt to experience a pregnancy that was wanted by only 1 spouse. Women who had difficulty discussing sexual matters with their husbands were more likely than other women to have a pregnancy that their husbands wanted but they did not.     

Organizational Compatibility and Workplace Drug Testing: Modeling the Adoption of Innovative Social Control Practices

Few researchers have examined organizational variation in the adoption of workplace drug testing, but innovation theory suggests that adoption is more likely when it is compatible with an organization's values, previously introduced ideas, and needs. Using data from the 1997 National Employee Survey, this research models the effects of organizational compatibility, industry, and establishment size on the adoption of drug testing. The data reveal that compatibility, as measured by an organization's rules orientation, presence of an employee assistance program, and mechanization, is associated with the adoption of drug testing. As predicted, the adoption of drug testing varies across industries and by establishment size.