The demand to initiate medical care: A morbidity specific analysis

The dependence of the one year probability of utilizing preventive services and the one year probability of utilizing visits for acute micro-organism disease in the Kaiser-Oregon Prepaid Medical Care System on ten (10) explanatory factors has been investigated using a multiple logistic function analysis.Our results demonstrate the importance of disaggregating the population and the type of medical care when investigating the determinants of utilizing service. This is especially important for understanding the underlying structure of medical care utilization decisions.The study also illustrates a potentially fruitful application of the multivariate logistic analysis to the fields of health care planning and policy analysis. The use of specific types of medical care in the short-term is probabilistic and depends on many factors. For most groups, the multivariate logistic approach produces an analysis reasonably consistent with the actual data.Further research is needed to test the predictive ability of these types of utilization models and to investigate the determinants of other morbidity specific types of medical care utilization. The problem will then be to develop a model of the quantity of alternative types of services utilized-conditioned on the number of persons initiating service for alternative health reasons.     

Organizational Effectiveness: An Empirical Comparision of the Goal and System Resource Approaches*

The goal and system resource approaches represent alternative conceptions of organizational effectiveness. The goal approach views effectiveness in terms of internal organizational objectives and performance. Organization-environment relations are the focus of the system resource approach, though previous applications of this perspective have been limited to profit-making organizations. This paper reconceptualizes the system resource approach for use in public agencies and examines the flow of organizational resources as an indicator of effectiveness. Goal approach indicators are matched with system resource measures in examining the convergence and consistency of the two approaches. The convergence of effectiveness measures is examined by observing the correlations between themselves and four organizational decision making variables that had previously been shown to be associated with effectiveness. An examination of the data collected through interviews with representatives of 110 public agencies reveals some consistency but no convergence between the two approaches.     

The family caregiving career: implications for community-based long-term care practice and policy

Informal (i.e., unpaid) long-term care for disabled older adults is often chronic, but it is only recently that research has considered the longitudinal implications of family caregiving. In particular, investigators have conceptualized caregiving as a "career," and within the caregiving career, a number of diverse trajectories and transitions can occur. Following a summary of these findings, this paper considers how longitudinal caregiving research can influence and potentially address key policy and practice concerns, especially in the delivery and support of community-based long-term care (CBLTC) services. It is suggested that with the refinement of the informal long-term care literature, existing policy and practice to support caregiving families can be similarly advanced.     

Beyond a Simple Case of Black and White: Searching for the White Male Effect in the African-American Community

Prior research focusing on risk perceptions has led to the observation that well‐educated and politically conservative white males tend to systematically perceive lower levels of risk from a wide range of hazards when compared to other members of society (e.g., white women, nonwhite women and men). While this “white male effect (WME)” is quite striking given that many policymakers fall into this group, a byproduct of this finding is that it deflects attention from the heterogeneity, in terms of people's concerns about risks, that exists in African‐American and other minority communities. The research reported here set out to explore this heterogeneity by asking a simple question: Can a phenomenon similar to the WME be found in the African‐American community? It can, and its implications for research and practice in risk management are discussed.     

Returns from the South: Effects of return migration of Ghanaian migrants from China on livelihoods and wealth inequalities in Ghana

The sedentary bias that characterizes discourses on migrations from and within the Global South has failed to inform a consistent exploration of international migration from and among global southern countries as normal, desirable and impactful to migrants and their social networks at different spatial levels. Migration-development nexus analyses are predominantly framed around Global South-Global North migration episodes whereby cash and social remittances from the North to the South are expected to trigger development in poorer global southern origin countries. This approach neglects the possibility of similar outcomes accruing from south-south migrations. Drawing on qualitative research methods among Ghanaian migrants to China, our paper addresses the question how does south-south migration affect livelihoods and wealth inequality? We argue that blunt global categorizations such as “Global South” and “Global North” only serve to obfuscate what is a rather heterogenous bunch of countries, with divergent opportunities for migrants. We recommend that greater focus should be on the contextual factors at the origin and destination, the quality of return preparedness and the human capital of the migrants rather than an arbitrary clustering around a binary Global South-Global North trajectory as though they are internally homogenous. We conclude that there is heterogeneity in the effects of south-south migration on household livelihoods and wealth inequalities.     

Testing Symmetry of the Error Distribution in Nonlinear Heteroscedastic Models

Using the empirical characteristic function, we derive a Cramér-von Mises test for symmetry of the error distribution in a class of nonlinear parametric heteroscedastic models. We study the convergence of the residual-based empirical distribution function. We establish a functional limit theorem for an empirical process of residuals, and investigate the asymptotic null distribution function of our test statistic. A simulation experiment is conducted to evaluate small-sample performances of our test.     

Age-period-cohort analysis: an illustration of the problems in assessing interaction in one observation per cell data

This paper discusses the specific problems of age-period-cohort (A-P-C) analysis within the general framework of interaction assessment for two-way cross-classified data with one observation per cell. The A-P-C multiple classification model containing the effects of age groups (rows), periods of observation (columns), and birth cohorts (diagonals of the two-way table) is characterized as one of a special class of models involving interaction terms assumed to have very specific forms. The so-called A-P-C identification problem, which results from the use of a particular interaction structure for detecting cohort effects, is shown to manifest itself in the form of an exact linear dependency among the columns of the design matrix. The precise relationship holding among these columns is derived, as is an explicit formula for the bias in the parameter estimates resulting from an incorrect specification of an assumed restriction on the parameters required to solve the normal equations. Current methods for modeling A-P-C data are critically reviewed, an illustrative numerical example is presented, and one potentially promising analysis strategy is discussed. However, gien the large number of possible sources for error in A-P-C analyses, it is strongly recommended that the results of such analyses be interpreted with a great deal of caution.     

A Survey of the Teaching of Statistics in M.B.A. Programs

A survey of business schools was conducted to obtain information about the current state of the teaching of business statistics to students enrolled in M.B.A. degree programs. The survey was undertaken for and presented at a June 1986 conference on “Making Statistics More Effective in Schools of Business,” held at the University of Chicago's Graduate School of Business. Information was elicited concerning both the required statistics sequence and elective statistics courses for M.B.A. students, as well as computer usage in these courses. This article summarizes the information obtained from the survey.     

Parametric Nonlinear Regression with Endogenous Switching

Based on the insightful work of Olsen (1980 Olsen , R. J. ( 1980 ). A least squares correction for selectivity bias . Econometrica 48 : 1815 – 1820 .[Crossref], [Web of Science ®] , [Google Scholar]) for the linear context, a generic and unifying framework is developed that affords a simple extension of the classical method of Heckman (1974 Heckman , J. ( 1974 ). Shadow prices, market wages, and labor supply . Econometrica 42 : 679 – 694 .[Crossref], [Web of Science ®] , [Google Scholar], 1976 Heckman , J. ( 1976 ). The common structure of statistical models of truncation sample selection and limited dependent variables and a simple estimator for such models . Annals of Economic and Social Measurement 5 : 475 – 492 . [Google Scholar], 1978 Heckman , J. ( 1978 ). Dummy endogenous variables in a simultaneous equation system . Econometrica 46 : 931 – 959 .[Crossref], [Web of Science ®] , [Google Scholar], 1979 Heckman , J. ( 1979 ). Sample selection bias as a specification error . Econometrica 47 : 153 – 161 .[Crossref], [Web of Science ®] , [Google Scholar]) to a broad class of nonlinear regression models involving endogenous switching and its two most common incarnations, endogenous sample selection and endogenous treatment effects. The approach should be appealing to applied researchers for three reasons. First, econometric applications involving endogenous switching abound. Secondly, the approach requires neither linearity of the regression function nor full parametric specification of the model. It can, in fact, be applied under the minimal parametric assumptions—i.e., specification of only the conditional means of the outcome and switching variables. Finally, it is amenable to relatively straightforward estimation methods. Examples of applications of the method are discussed.