Academic Affiliations of Those Published in Social Work Journals: A Productivity Analysis, 1989–1993

Abstract

The academic affiliations of the authors of all articles published in six social work journals between 1989 and 1993 were reviewed and tabulated to produce a ranking of the colleges and universities whose faculty are making the most substantive contributions to the social work literature. The results of this analysis are compared with the findings of two similar, previously published studies covering the five-year periods of 1979-1983 and 1984-1988.     

Iterative regularisation in nonparametric instrumental regression

This paper considers the nonparametric regression model with an additive error that is correlated with the explanatory variables. Motivated by empirical studies in epidemiology and economics, it also supposes that valid instrumental variables are observed. However, the estimation of a nonparametric regression function by instrumental variables is an ill-posed linear inverse problem with an unknown but estimable operator. We provide a new estimator of the regression function that is based on projection onto finite dimensional spaces and that includes an iterative regularisation method (the Landweber–Fridman method). The optimal number of iterations and the convergence of the mean square error of the resulting estimator are derived under both strong and weak source conditions. A Monte Carlo exercise shows the impact of some parameters on the estimator and concludes on the reasonable finite sample performance of the new estimator.     

Social Cohesion and the Labour Market: Societal Regimes of Civic Attitudes and Labour Market Regimes

The aim of this paper is to test the connections between the indicators used in the literature on social cohesion, which usually reflect ‘general’ values or behaviours, and indicators specific to a particular space, namely the labour market. A key question is the stability of the social cohesion’s indicators when moving from a societal level to the labour market. Based on data from the World Value Survey, and following a restrictive definition of social cohesion, a comparison is done, for European countries. Examination of the situation in the two spheres makes it possible to identify more or less homogeneous groups of countries and also to point to instabilities. ‘Regimes’ of social cohesion begin to emerge. As in most analyses, the Nordic countries (excluding Finland) have high scores in all the dimensions. Conversely, most of the new EU member states from the former Eastern bloc have low scores, particularly in the horizontal dimension of trust between individuals.     

Testing the relationship between income inequality and life expectancy: a simple correction for the aggregation effect when using aggregated data

In this paper, we show a simple correction for the aggregation effect when testing the relationship between income inequality and life expectancy using aggregated data. While there is evidence for a negative correlation between income inequality and a population’s average life expectancy, it is not clear whether this is due to an aggregation effect based on a non-linear relationship between income and life expectancy or to income inequality being a health hazard in itself. The proposed correction method is general and independent of measures of income inequality, functional form assumptions of the health production function, and assumptions on the income distribution. We apply it to data from the Human Development Report and find that the relationship between income inequality and life expectancy can be explained entirely by the aggregation effect. Hence, there is no evidence that income inequality itself is a health hazard.     

A Novel Time Series Approach to Bridge Coding Changes with a Consistent Solution Across Causes of Death

Revisions of the International Classification of Diseases (ICD) can lead to biases in cause-specific mortality levels and trends. We propose a novel time series approach to bridge ICD coding changes which provides a consistent solution across causes of death. Using a state space model with interventions, we performed time series analysis to cause-proportional mortality for ICD9 and ICD10 in the Netherlands (1979–2010), Canada (1979–2007) and Italy (1990–2007) on chapter level. A constraint was used to keep the sum of cause-specific interventions zero. Comparability ratios (CRs) were estimated and compared to existing bridge coding CRs for Italy and Canada. A significant ICD9 to ICD10 transition occurred among 13 cause of death groups in Italy, 7 in Canada and 3 in the Netherlands. Without the constraint, all-cause mortality after the classification change would be overestimated by 0.4 % (NL), 0.03 % (Canada) and 0.2 % (Italy). The time series CRs were in the same direction as the bridge coding CRs but deviated more from 1. A smooth corrected trend over the ICD-transition resulted from applying the time series approach. Comparing the time series CRs for Italy (2003), Canada (1999) and the Netherlands (1995) revealed interesting commonalities and differences. We demonstrated the importance of adding the constraint, the validity of our methodology and its advantages above earlier methods. Applying the method to more specific causes of death and integrating medical content to a larger extent is advocated.     

Confidence Regions Based on Edgeworth Expansion

We describe a procedure for constructing accurate confidence regions by first expanding the sampling distribution of parameter estimators in an Edgeworth series, then eliminating the beyond-normal terms by a simple polynomial transformation. We demonstrate this using the two-parameter Cauchy and Weibull distributions.     

Guaranteed Conditional Performance of Control Charts via Bootstrap Methods

To use control charts in practice, the in‐control state usually has to be estimated. This estimation has a detrimental effect on the performance of control charts, which is often measured by the false alarm probability or the average run length. We suggest an adjustment of the monitoring schemes to overcome these problems. It guarantees, with a certain probability, a conditional performance given the estimated in‐control state. The suggested method is based on bootstrapping the data used to estimate the in‐control state. The method applies to different types of control charts, and also works with charts based on regression models. If a non‐parametric bootstrap is used, the method is robust to model errors. We show large sample properties of the adjustment. The usefulness of our approach is demonstrated through simulation studies.     

Review of Five Multilevel Analysis Programs: BMDP-5V,GENMOD, HLM,ML3, VARCL

A class of statistics is introduced for testing stochastic ordering between two independent distributions. This class includes as a special case the celebrated Mann—Whitney—Wilcoxon statistic. The new class is shown to be asymptotically normal both under the null and nonnull hypotheses. It is distribution-free. Using Pitman's asymptotic efficacy it is shown that for some alternatives the Mann—Whitney—Wilcoxon statistic is the member with the highest efficacy, although for others it is not, and the member with the highest efficacy is identified.     

Testing the equality of several means when the population variances are unequal

A comparative study is made of three tests, developed by James (1951), Welch (1951) and Brown & Forsythe (1974). James presented two methods of which only one is considered in this paper. It is shown that this method gives better control over the size than the other two tests. None of these methods is uniformly more powerful than the other two. In some cases the tests of James and Welch reject a false null hypothesis more often than the test of Brown & Forsythe, but there are also situations in which it is the other way around.

We conclude that for implementation in a statistical software package the very complicated test of James is the most attractive. A practical disadvantage of this method can be overcome by a minor modification.     

Generalized Kernel Estimators for the Weibull-Tail Coefficient

We introduce new families of estimators for the Weibull-tail coefficient, obtained from a weighted sum of a power transformation of excesses over a high random threshold. Asymptotic normality of the estimators is proven for an intermediate sequence of upper order statistics, and under classical regularity conditions for L-statistics and a second-order condition on the tail behavior of the underlying distribution. The small sample performance of two specific examples of kernel functions is evaluated in a simulation study.