On the existence and uniqueness of the NPMLE in biased sampling models

Identifiability, existence and uniqueness of the non-parametric maximum likelihood estimator (NPMLE) in biased sampling models are thoroughly investigated. The conditions for existence and uniqueness are considered from a different perspective and proofs are simplified. An extension to semi-parametric models is provided.     

The Stability and Change of Value Structure and Priorities in Childhood: A Longitudinal Study

This longitudinal study explores the stability and change of values in childhood. Children's values were measured in Poland three times (with one‐year intervals) using the Picture Based Values Survey (PBVS‐C; Döring, Blauensteiner, Aryus, Drögekamp, & Bilsky, 2010), developed to measure values differentiated according to the circular model of Schwartz (1992). 801 children (divided into 5 cohorts aged 7, 8, 9, 10, and 11 years at the first measurement occasion) completed the PBVS‐C three times on a yearly basis. Separate analyses were performed for each cohort using the data of the three measurement occasions. Multidimensional scaling revealed that, in children, Schwartz's (1992) circular structure of values is stable and does not change over time. Although priorities of values displayed moderate stability over time, the means changed between the ages of 7 and 11 years. Specifically, latent growth curve modeling revealed changes in children's values hierarchy as indicated by the decrease in the mean level of conservation values and the increase in the mean level of openness to change values. Self‐transcendence and self‐enhancement also changed in different directions. As indicated by mean levels over time, self‐transcendence first increased in importance, slightly decreased, and finally increased again. In contrast, self‐enhancement first decreased in importance, then increased, and finally began to decrease again.     

The Syndrome of Group-Focused Enmity: The Interrelation of Prejudices Tested with Multiple Cross-Sectional and Panel Data

Different types of prejudice are usually treated as separate constructs. We propose that they constitute a syndrome of group-focused enmity (GFE), that is, they are related to each other and share a common core that is strongly predicted by a generalized ideology of inequality. Furthermore, GFE components are supposed to have similar predictors and outcomes. An empirical test is presented using structural equation modeling on the syndrome, its causes, consequences, and structural stability over time. The study relies on three German cross-sectional probability samples (each N = 2,700) and a related panel study (2002, 2003, and 2004). The idea of a GFE syndrome is strongly supported. Future research is discussed, as well as alternative approaches of a common prejudice factor .     

Order restricted inference for multivariate binary data with application to toxicology

In many applications researchers collect multivariate binary response data under two or more, naturally ordered, experimental conditions. In such situations one is often interested in using all binary outcomes simultaneously to detect an ordering among the experimental conditions. To make such comparisons we develop a general methodology for testing for the multivariate stochastic order between K ≥ 2 multivariate binary distributions. The proposed test uses order restricted estimators which, according to our simulation study, are more efficient than the unrestricted estimators in terms of mean squared error. The power of the proposed test was compared with several alternative tests. These included procedures which combine individual univariate tests for order, such as union intersection tests and a Bonferroni based test. We also compared the proposed test with unrestricted Hotelling's T(2) type test. Our simulations suggest that the proposed method competes well with these alternatives. The gain in power is often substantial. The proposed methodology is illustrated by applying it to a two-year rodent cancer bioassay data obtained from the US National Toxicology Program (NTP). Supplemental materials are available online.     

Representing representations: the ethics of filming at Ground Zero

In this paper I analyse the ethical challenges that informed the production and filming of my documentary September Signs and Symbols. The film focuses on the material objects that commemorate the terrorist attacks of 9/11, and how this memorabilia circulates in New York City. The film explores how these objects have come to be complex signifiers containing within them the possibility for a range of meanings for people who create them, sell them, collect them, and use them and this paper reflects on the complex ethics of filming at Ground Zero – a highly charged political and cultural site. I analyse the ethics of representing a hyper‐represented space, the necessity for self‐reflexivity in the process of demystifying signifiers that have had meaning appended to them and my own complicity in the dialectic of production and consumption that informs any engagement with the objectified discourse of September 11th.     

Ordered Regressions

There are often situations where two or more regression functions are ordered over a range of covariate values. In this paper, we develop efficient constrained estimation and testing procedures for such models. Specifically, necessary and sufficient conditions for ordering generalized linear regressions are given and shown to unify previous results obtained for simple linear regression, for polynomial regression and in the analysis of covariance models. We show that estimating the parameters of ordered linear regressions requires either quadratic programming or semi‐infinite programming, depending on the shape of the covariate space. A distance‐type test for order is proposed. Simulations demonstrate that the proposed methodology improves the mean square error and power compared with the usual, unconstrained, estimation and testing procedures. Improvements are often substantial. The methodology is extended to order generalized linear models where convex semi‐infinite programming plays a role. The methodology is motivated by, and applied to, a hearing loss study.     

Individual values,cultural embeddedness,and anti-immigration sentiments: Explaining differences in the effect of values on attitudes toward immigration across Europe

During the last decade, many European countries have faced sizeable immigration inflows accompanied by high prevalence of negative sentiments toward immigrants among majority members of the host societies. We propose that basic human values are one important determinant of such negative attitudes, and we seek to explain variation across countries in the strength of the effects of values. Based on Schwartz’ (1992, 1994) basic human value theory, we hypothesize that universalism values are conducive to positive attitudes toward immigration, while conformity-tradition reinforce anti-immigration sentiments. We furthermore hypothesize that these value effects are moderated by two contextual variables. Both value effects are expected to be weaker in countries with a higher level of cultural embeddedness. Furthermore, negative effects of conformity-tradition values are hypothesized to be cushioned by a lower proportion of immigrants in the country. A multilevel analysis of data from 24 countries from the fourth round of the European Social Survey (2008–2009) supports these hypotheses. Moreover, we demonstrate that the measurement properties of the theoretical constructs exhibit equivalence across countries, thereby justifying statistical comparisons.     

Semiparametric Inference for the Two‐way Layout Under Order Restrictions

There are many situations in which a researcher would like to analyse data from a two‐way layout. Often, the assumptions of linearity and normality may not hold. To address such situations, we introduce a semiparametric model. The model extends the well‐known density ratio model from the one‐way to the two‐way layout and provides a useful framework for semiparametric analysis of variance type problems under order restrictions. In particular, the likelihood ratio order is emphasized. The model enables highly efficient inference without resorting to fully parametric assumptions or the use of transformations. Estimation and testing procedures under order restrictions are developed and investigated in detail. It is shown that the model is robust to misspecification, and several simulations suggest that it performs well in practice. The methodology is illustrated using two data examples; in the first, the response variable is discrete, whereas in the second, it is continuous.