Sampling Strategies for Toxic Air Contaminants

Annual concentrations of toxic air contaminants are of primary concern from the perspective of chronic human exposure assessment and risk analysis. Despite recent advances in air quality monitoring technology, resource and technical constraints often impose limitations on the availability of a sufficient number of ambient concentration measurements for performing environmental risk analysis. Therefore, sample size limitations, representativeness of data, and uncertainties in the estimated annual mean concentration must be examined before performing quantitative risk analysis. In this paper, we discuss several factors that need to be considered in designing field-sampling programs for toxic air contaminants and in verifying compliance with environmental regulations. Specifically, we examine the behavior of SO2, TSP, and CO data as surrogates for toxic air contaminants and as examples of point source, area source, and line source-dominated pollutants, respectively, from the standpoint of sampling design. We demonstrate the use of bootstrap resampling method and normal theory in estimating the annual mean concentration and its 95% confidence bounds from limited sampling data, and illustrate the application of operating characteristic (OC) curves to determine optimum sample size and other sampling strategies. We also outline a statistical procedure, based on a one-sided t-test, that utilizes the sampled concentration data for evaluating whether a sampling site is compliance with relevant ambient guideline concentrations for toxic air contaminants.     

African American Women's Self-Concept: Implications for Career Decisions and Career Counseling

The multiple self-referent model (Brown-Collins & Sussewell, 1986) provides a comprehensive framework for understanding the personal, social, and historical aspects of self-concept formation in African American women and has important implications for understanding the complexity of career development issues for Black women. Excerpts from recorded interviews and autobiographical writings of four well-known African American women provide examples of the basic components of this model. Suggested interventions for career counseling with Black female clients are discussed.     

Grounded Neural Networking: Modeling Complex Quantitative Data

The latest advances in artificial intelligence software (neural networking) have finally made it possible for qualitative researchers to apply the grounded theory method to the study of complex quantitative databases in a manner consistent with the postpositivistic, neopragmatic assumptions of most symbolic interactionists. The strength of neural networking for the study of quantitative data is twofold: it blurs the boundaries between qualitative and quantitative analysis, and it allows grounded theorists to embrace the complexity of quantitative data. The specific technique most useful to grounded theory is the Self‐Organizing Map (SOM). To demonstrate the utility of the SOM we (1) provide a brief review of grounded theory, focusing on how it was originally intended as a comparative method applicable to both quantitative and qualitative data; (2) examine how the SOM is compatible with the traditional techniques of grounded theory; and (3) demonstrate how the SOM assists grounded theory by applying it to an example based on our research.     

Surname analysis for estimating local concentration of Hispanics and Asians

Surname analysis is a potentially useful technique for identifying members of particular racial, ethnic, or language communities within a population. We review the existing state of the art for identifying persons of Hispanic or Asian origin, based on surnames distinctive of each group. We describe the logic of surname analysis, profile several available surname dictionaries, and illustrate their applications in local redistricting. Results of our ongoing validation studies suggest promising future directions for improving accuracy and broadening applications.This article is based on a paper presented at the annual Population Association of America meetings at Cincinnati, 1 April 1993.     

A discordant consolidation of the self in a late adolescent male

A distinction is made between the cohesive self and the nuclear self. The latter represents a consolidation of the self that occurs in late adolescence and that results from the integration of life goals and ambitions into a coherent narrative. This paper presents a case in which a pseudo-consolidation appears to have occurred in an adolescent with an undiagnosed learning disability.Ms. Silbar is in private practice.     

The transition to parenthood in Puerto Rico: Occupational status and the timing of first births

This study examines the relationship between occupational status and fertility timing during a period of rapid development in Puerto Rico. Our fundamental hypothesis is that women with higher status occupations face greater opportunity costs than those with less valued jobs and therefore will be more likely to postpone parenthood until later ages than women without such high costs. We test this hypothesis using event history techniques with data from the 1982 Puerto Rico Fertility and Family Planning Assessment, an island-wide survey of women between the ages of 15 and 49. The analysis examines the effects of occupational status on the timing of first births, and finds strong support for the basic hypothesis, especially regarding the post-ponement of teen births. After the teen years, the effects are less pronounced. Overall, it appears that employment opportunities have played an important role in childbearing decisions in Puerto Rico.An earlier version of this paper was presented at the annual meeting of the Population Association of America, Denver, Colorado, 30 April–2 May 1992.     

The validity of survey responses on abortion: Evidence from Estonia

This paper presents results of a validation survey of abortion conducted in Tallinn, Estonia in April and May 1992. The sample was drawn from patient records in a maternity hospital. Women who had an abortion in that hospital in 1991 were asked about recent abortions as part of a survey about women’s health. More than 80% of the respondents reported having a recent abortion. Some respondents misreported their abortion as a miscarriage. Moreover, some variation in reporting was associated with respondents’ characteristics. Ethnic Estonians were less likely to report their abortion than were Russians, women over age 40 were less likely to report the abortion than younger women, and women who had the abortion late in the first trimester were less likely to report that abortion. There was some evidence that unmarried women were less likely than married women to report their abortion, and that women who had borne three or more children were less likely to report their abortion than women who had borne fewer children. These differences probably stem from the extent to which pregnancy or abortion is considered stigmatizing for women in different situations.     

Local polynomial estimation of Poisson intensities in the presence of reporting delays

Summary.  The system for monitoring suicides in Hong Kong has considerable delays in reporting as the cause of death needs to be determined by a coroner's investigation. However, timely estimates of suicide rates are desirable to assist in the formulation of public health policies. This motivated us to develop a non-parametric procedure to estimate the intensity function of a Poisson process in the presence of reporting delays. We give closed form estimators of the Poisson intensity and the delay distribution, conduct simulation studies to evaluate the method proposed and derive their asymptotic properties. The method proposed is applied to estimate the intensity of suicide in Hong Kong.     

Bayesian analysis of directed graphs data with applications to social networks

Summary.  A fully Bayesian analysis of directed graphs, with particular emphasis on applica- tions in social networks, is explored. The model is capable of incorporating the effects of covariates, within and between block ties and multiple responses. Inference is straightforward by using software that is based on Markov chain Monte Carlo methods. Examples are provided which highlight the variety of data sets that can be entertained and the ease with which they can be analysed.