Divergence-based estimation and testing with misclassified data

The well-known chi-squared goodness-of-fit test for a multinomial distribution is generally biased when the observations are subject to misclassification. In Pardo and Zografos (2000) the problem was considered using a double sampling scheme and ø-divergence test statistics. A new problem appears if the null hypothesis is not simple because it is necessary to give estimators for the unknown parameters. In this paper the minimum ø-divergence estimators are considered and some of their properties are established. The proposed ø-divergence test statistics are obtained by calculating ø-divergences between probability density functions and by replacing parameters by their minimum ø-divergence estimators in the derived expressions. Asymptotic distributions of the new test statistics are also obtained. The testing procedure is illustrated with an example.     

Generalized additive models for location, scale and shape

Summary.  A general class of statistical models for a univariate response variable is presented which we call the generalized additive model for location, scale and shape (GAMLSS). The model assumes independent observations of the response variable y given the parameters, the explanatory variables and the values of the random effects. The distribution for the response variable in the GAMLSS can be selected from a very general family of distributions including highly skew or kurtotic continuous and discrete distributions. The systematic part of the model is expanded to allow modelling not only of the mean (or location) but also of the other parameters of the distribution of y , as parametric and/or additive nonparametric (smooth) functions of explanatory variables and/or random-effects terms. Maximum (penalized) likelihood estimation is used to fit the (non)parametric models. A Newton–Raphson or Fisher scoring algorithm is used to maximize the (penalized) likelihood. The additive terms in the model are fitted by using a backfitting algorithm. Censored data are easily incorporated into the framework. Five data sets from different fields of application are analysed to emphasize the generality of the GAMLSS class of models.     

Proportional reversed hazard rate model and its applications

The purpose of this paper is to study the structure and properties of the proportional reversed hazard rate model (PRHRM) in contrast to the celebrated proportional hazard model (PHM). The monotonicity of the hazard rate and the reversed hazard rate of the model is investigated. Some criteria of aging are presented and the inheritance of the aging notions (of the base distribution) by the PRHRM is studied. Characterizations of the model involving Fisher information are presented and the statistical inference of the parameters is discussed. Finally, it is shown that several members of the proportional reversed hazard rate class have been found to be useful and flexible in real data analysis.     

Culturalising the Abject: Islam,Law and Moral Panic in the West

This paper explores the construction of Islam as abject and the symbolic positioning of Muslims as being outside secular modernity in Australia through an analysis of the way the criminal legal process and perceptions of criminality are culturalised. The empirical focus is gang rape and the trials of Muslim youth on gang rape charges in Sydney between 2000–2003 which quickly became culturally inflected as ‘Muslim’ and ‘Lebanese’ by media reporting of the criminal trials and moral panic about them as source of social menace. Three dimensions of culturalisation of crime and the criminalisation of culture are identified in the criminal legal process and media reporting of it; firstly the cultural inflection of new laws against gang rape by their association with particular events and trials; secondly the introduction of ‘cultural defence’ by the accused as a mitigating factor in the criminal legal process; thirdly, media reporting and commentary on criminal cases which emphasize cultural explanations for individual criminal behaviour.     

Population constraints on pooled surveys in demographic hazard modeling

In non-experimental research, data on the same population process may be collected simultaneously by more than one instrument. For example, in the present application, two sample surveys and a population birth registration system all collect observations on first births by age and year, while the two surveys additionally collect information on women’s education. To make maximum use of the three data sources, the survey data are pooled and the population data introduced as constraints in a logistic regression equation. Reductions in standard errors about the age and birth-cohort parameters of the regression equation in the order of three-quarters are obtained by introducing the population data as constraints. A halving of the standard errors about the education parameters is achieved by pooling observations from the larger survey dataset with those from the smaller survey. The percentage reduction in the standard errors through imposing population constraints is independent of the total survey sample size.     

Family Cap and Nonmarital Fertility: The Racial Conditioning of Policy Effects

Using an experimental design, this research examines the effect of the nation's first family cap on the births, abortions, and contraception use of over 8,000 women receiving public assistance in New Jersey. The family cap denies additional cash benefits to children conceived while the mother is receiving public assistance. Our research shows that a targeted welfare benefit manipulation does influence fertility behavior; however, the effect is conditioned by race. We find that Black women in the experimental group have a 21% lower birth rate and a 32% higher abortion rate than Black women in the control group. We do not find a birth effect for Hispanic or White women. We discuss the policy implications of the effects of a segmented family cap.     

A simple procedure for the selection of significant effects

Summary.  Given a large number of test statistics, a small proportion of which represent departures from the relevant null hypothesis, a simple rule is given for choosing those statistics that are indicative of departure. It is based on fitting by moments a mixture model to the set of test statistics and then deriving an estimated likelihood ratio. Simulation suggests that the procedure has good properties when the departure from an overall null hypothesis is not too small.     

Farming Patterns,Rural Restructuring,and Poverty: A Comparative Regional Analysis1

Abstract This study examines the contentions of two recent perspectives on rural economic organization and their implications for poverty. Building from (1) agrarian political economy and (2) the rural restructuring literatures, we present a comparative regional analysis of how farming patterns and other aspects of economic organization differentially affect poverty in rural areas. Data are based on 2,349 nonmetropolitan U.S. counties for the 1970–1980 period. Nonhired labor-dependent, family-operated farming (smaller and larger family farming) has relatively similar cross-regional effects on rural poverty. The effects of industrialized farming are more spatially variant, suggesting that this type of farming is integrated into regional political economies in different ways than are simple commodity units. However, farming patterns have only a small effect on rural poverty relative to other factors, such as the local employment structure, characteristics of the population, and geographic location. The results of this study highlight the need to move beyond the farm sector to understand both the dynamics of this sector and the socioeconomic consequences of rural restructuring. More broadly, the study underscores the importance of testing general sociological relationships under different spatial (e.g., regional) contexts.     

Ethnic preferences and perceptions among Asian and White British middle school children

Asian and White middle school children were shown photographs of unknown Afro-Caribbean, Asian, and White individuals of approximately the same age as themselves, and asked which one wax most like them, which one they would prefer to be, which ones they would prefer to engage in various activities with, and finally, to allocate positive and negative traits to the three groups or to nobody. A similar majority of both Asian and While children selected an own-race photograph as being most like them, but only about a half selected the own-race photograph as the one they would most like to he. For sharing activities, children showed a strong own-tender preference, followed by an own-race preference. White children stated a greater preference for sharing activities with White children, then with Afro-Caribbean children, and least with Asian children. Asian children preferred Asian and White children the most, Afro-Caribbean the least. On a stereotypes test, similar trends were obtained; White children evaluated While children highest and Asian lowest; Asian children tended to evaluate Asian children highest but to a nonsignificant extent. The relative proportion of Asian/White children in school appeared to have little systematic influence on the results, thus arguing against the contact hypothesis of prejudice reduction in its simple form.