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.     

Demographic Shifts in the Czech Republic after 1989: A Second Demographic Transition View

A dramatic change in fertility,family formation and living arrangements tookplace in the Czech Republic over the 1990s. Theestablishment of democracy, profound socialtransformation and transition to the marketeconomy affected the values and demographicbehaviour of the young Czech generation. Thispaper examines whether these demographic shiftscan be interpreted within the framework of thesecond demographic transition. The theoreticalpart discusses the idea of the transition,outlining three distinctive conceptualisations.Two of them – the view of the transition as aprogression of characteristic interrelateddemographic changes and a broader viewstressing the importance of underlyingideational factors – fit the Czech situationvery well. A comparison with the Netherlandsreveals that the onset of the transition in theCzech Republic may be clearly located in thefirst half of the 1990s, lagging two decadesbehind the Netherlands.     

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.     

The gambling market in the Federal Republic of Germany and the helpseeking of pathological gamblers

The development of the gambling market in the Federal Republic of Germany since the middle of the seventies and data on pathological gamblers seeking help are described. The continuously increasing supply, together with increases in turnover, was followed-with some temporal delay-by an increase in the number of gamblers who sought advice and treatment. Preliminary measures taken by the health authorities as well as some consequences of pathological gambling are discussed.This article is a translation of a German article published in: Deutsche Hauptstelle gegen die Suchtgefahren (1990): Jahrbuch '91 zur Frage der Suchtgefahren. Hamburg: Neuland-Verlag.     

Toward a formal theory of interactive resocialization: The case of adoptive parenthood

Resocialization is pulled out of its structuralist roots and recast into an interactionist framework. Building on a substantive theory of the resocialization experience of becoming an adoptive parent, three theoretical properties of interactionist resocialization are presented. These can be summarized as involving unlearning and relearning some aspects of a core identity; the interpretation and active reconstruction of that identity which has reciprocal effects on all actors involved; and finally, the effects of both situational and trans-situational norms that give shape to the resocialization experience. Suggestions are made for other substantive areas of research that could be used for comparative analysis in order to further refine a formal theory of interactionist resocialization.