Media Publicity and the Voluntary Sector: The Case of Nonprofit Organizations in New York City

Media publicity is an important resource for contemporary voluntary associations, but very little is actually known about the resources and organizational characteristics that are most important for getting media attention. To address this question, we collected and analyzed data on the organizational attributes and news publicity of 739 nonprofit organizations in New York City. We find that an organization's income, paid staff, membership size, and library resources are significantly related to getting media publicity, whereas the number of chapter affiliations is inversely related to publicity. Association type is also a significant factor that influences an organization's ability to get publicity. We discuss the implications that these findings have for current debates about advocacy and civic engagement in the nonprofit sector.     

The Role of Household Social Organization in the Structure of Rural Economies: Comparing Forest Resource Dependent and Agriculturally Dependent Regions in Russia

Sociologists have examined how structural economic change affects household social organization and generation of household income from different sources. The introduction of elements of a market economy into rural Russia in the early 1990s provides a unique opportunity to examine these relationships. Much of the work on this topic, however, has been conducted in black earth zone, agriculturally dependent regions. Less attention has been given to non‐black‐earth zone, forest resource dependent regions. This article addresses this limitation by comparing the relationships between household income generation strategies and household social organization in a 2009 survey of villages in three forest resource dependent regions in northwest Russia with findings from a 2006 survey of households in nine agricultural regions of Russia. Income generated from enterprises based on household social organization—household labor and social helping networks—is substantially greater in agriculturally dependent than in forest resource dependent regions. We discuss the implications of these findings for understanding intranational regional differences in the relationship between economic systems, household social organization, and rural household economies as well as the obstacles facing policymakers and environmentalists who attempt to shift household income generation strategies away from an environmentally harmful lumber industry to income generation activities that are less harmful to the environment.     

The production of criminological experiments

This article examines the production of crime and justice field experiments during the 1990s. Data were collected on the characteristics of criminological experiments funded by the National Institute of Justice (NIJ), the principal research agency of the U.S. Department of Justice, during the 10-year period from 1991 through 2000. The analyses find that, whereas the funds available for research and evaluation at the NIJ increased during this period, the number of projects and the amount of funds awarded supporting field experiments declined. The article describes the characteristics of the experiments funded and assesses the extent to which the reduced support can be attributed to the characteristics of NIJ research funding, research topics, researchers, or criminal justice operational agencies.     

Reporting cumulative proportion of subjects with an adverse event based on data from multiple studies

Experience has shown us that when data are pooled from multiple studies to create an integrated summary, an analysis based on naïvely‐pooled data is vulnerable to the mischief of Simpson's Paradox. Using the proportions of patients with a target adverse event (AE) as an example, we demonstrate the Paradox's effect on both the comparison and the estimation of the proportions. While meta analytic approaches have been recommended and increasingly used for comparing safety data between treatments, reporting proportions of subjects experiencing a target AE based on data from multiple studies has received little attention. In this paper, we suggest two possible approaches to report these cumulative proportions. In addition, we urge that regulatory guidelines on reporting such proportions be established so that risks can be communicated in a scientifically defensible and balanced manner. Copyright © 2010 John Wiley & Sons, Ltd.     

Multiplicative-interaction logit models for i×j×2 three-way tables

Multiplicative-interaction (M-I) logit models are proposed for three-way IxJx2 contingency tables where the third variable constitutes a binary response. Models are derived by assigning unknown scores to the categories and forming product interactions from them. Asymptotic results under special sampling constraints are derived for maximum likelihood estimates and the goodness-of-fit statistics. The class of models proposed in this paper are found to be useful when no obvious scores are available. An example is included.     

Pseudo maximum likelihood estimation for the dirichlet-multinomial distribution

Pseudo maximum likelihood estimation (PML) for the Dirich-let-multinomial distribution is proposed and examined in this pa-per. The procedure is compared to that based on moments (MM) for its asymptotic relative efficiency (ARE) relative to the maximum likelihood estimate (ML). It is found that PML, requiring much less computational effort than ML and possessing considerably higher ARE than MM, constitutes a good compromise between ML and MM. PML is also found to have very high ARE when an estimate for the scale parameter in the Dirichlet-multinomial distribution is all that is needed.     

Some simple log-linear models for the analysis of ordinal response data

A family of log-linear models are proposed to describe contingency tables in which one variable can be considered as the response to the remaining. The proposed models take into account the ordering nature of the response categories and have structure similar to that employed in polynomial regression. Stochastic ordering of the response distributions under the proposed models is discussed and the model-reduction techniques are developed. The proposed models are applied to two data sets previously analysed in the literature.