The influence of faith‐based organisations on Australian social policy

This historical overview explores the crucial and changing relationships between faith‐based organisations and governments, not only in the implementation of social services but also in the formation of social policy. Historically Australian governments have left large areas of social provision to the non‐government sector. For example, income support for the unemployed was not taken up by governments until World War II and income support for sole parents remained largely a responsibility for non‐government organisations (NGOs) until the 1970s. Prior to governments taking responsibility for income support, most of these NGOs were religious organisations surviving on donations, philanthropic support and limited government funding. It is argued that the dominant, semi‐public role of religious organisations in service delivery and social policy formation is an important but largely overlooked aspect of the Australian historical experience.     

Parent–child negative emotion reciprocity and children's school success: An emotion‐attention process model

Research has demonstrated that emotions expressed in parent–child relationships are associated with children's school success. Yet the types of emotional expressions, and the mechanisms by which emotional expressions are linked with children's success in school, are unclear. In the present article, we focused on negative emotion reciprocity in parent–child interactions. Using structural equation modeling of data from 138 parent to child dyads [children's mean age at Time 1 (T1) was 13.44 years, SD = 1.16], we tested children's negative emotionality (CNE) at T1 and low attention focusing (LAF) at Time 2 (T2) as sequential mediators in the relation between parent and child negative emotion reciprocity at T1 and children's grade point average (GPA) and inhibitory control at T2. Our findings supported an emotion‐attention process model: parent–child negative emotion reciprocity at T1 predicted CNE at T1, which predicted children's LAF at T2, which was, in turn, related to low inhibitory control at T2. Findings regarding children's GPA were less conclusive but did suggest an overall association of negative reciprocity and the two mediators with children's GPA. Our findings are discussed in terms of emotion regulation processes in children from negatively reciprocating dyads, and the effects of these processes on children's ability to obtain and use skills needed for success in school.     

A joint model for hierarchical continuous and zero-inflated overdispersed count data

Many applications in public health, medical and biomedical or other studies demand modelling of two or more longitudinal outcomes jointly to get better insight into their joint evolution. In this regard, a joint model for a longitudinal continuous and a count sequence, the latter possibly overdispersed and zero-inflated (ZI), will be specified that assembles aspects coming from each one of them into one single model. Further, a subject-specific random effect is included to account for the correlation in the continuous outcome. For the count outcome, clustering and overdispersion are accommodated through two distinct sets of random effects in a generalized linear model as proposed by Molenberghs et al. [A family of generalized linear models for repeated measures with normal and conjugate random effects. Stat Sci. 2010;25:325–347]; one is normally distributed, the other conjugate to the outcome distribution. The association among the two sequences is captured by correlating the normal random effects describing the continuous and count outcome sequences, respectively. An excessive number of zero counts is often accounted for by using a so-called ZI or hurdle model. ZI models combine either a Poisson or negative-binomial model with an atom at zero as a mixture, while the hurdle model separately handles the zero observations and the positive counts. This paper proposes a general joint modelling framework in which all these features can appear together. We illustrate the proposed method with a case study and examine it further with simulations.     

Regression analysis of longitudinal data with outcome‐dependent sampling and informative censoring

We consider a regression analysis of longitudinal data in the presence of outcome‐dependent observation times and informative censoring. Existing approaches commonly require a correct specification of the joint distribution of longitudinal measurements, the observation time process, and informative censoring time under the joint modeling framework and can be computationally cumbersome due to the complex form of the likelihood function. In view of these issues, we propose a semiparametric joint regression model and construct a composite likelihood function based on a conditional order statistics argument. As a major feature of our proposed methods, the aforementioned joint distribution is not required to be specified, and the random effect in the proposed joint model is treated as a nuisance parameter. Consequently, the derived composite likelihood bypasses the need to integrate over the random effect and offers the advantage of easy computation. We show that the resulting estimators are consistent and asymptotically normal. We use simulation studies to evaluate the finite‐sample performance of the proposed method and apply it to a study of weight loss data that motivated our investigation.     

A GENEALOGY OF CORRESPONDENCE ANALYSIS

Over the past half a century correspondence analysis has grown from a little known statistical technique designed to graphically depict the association structure of categorical variables that form a contingency table to a very popular tool used in a wide variety of disciplines. Despite this growth, correspondence analysis remains relatively unknown in some parts of the world, including the Australasian statistical community. This paper provides a non‐technical, bibliographic exploration of correspondence analysis. We take a step back to view the development of this statistical technique and provide a brief account of its genealogy with a selection of over 270 key publications that have contributed to its growth. We also look at its maturity over the decades.     

Binomial confidence limits adjusted for a confounding variable

A simple transformation of classical binomial confidence limits provides exact confidence limits in situations where a confounding variable is present. An example is the multiple-choice test, where a correct answer may represent either knowledge or guesswork, the latter being the confounding variable.     

Weighted Marshall–Olkin bivariate exponential distribution

Recently, Gupta and Kundu [R.D. Gupta and D. Kundu, A new class of weighted exponential distributions, Statistics 43 (2009), pp. 621–634] have introduced a new class of weighted exponential (WE) distributions, and this can be used quite effectively to model lifetime data. In this paper, we introduce a new class of weighted Marshall–Olkin bivariate exponential distributions. This new singular distribution has univariate WE marginals. We study different properties of the proposed model. There are four parameters in this model and the maximum-likelihood estimators (MLEs) of the unknown parameters cannot be obtained in explicit forms. We need to solve a four-dimensional optimization problem to compute the MLEs. One data set has been analysed for illustrative purposes and finally we propose some generalization of the proposed model.     

Nonparametric approaches to testing and multiple comparisons in a one-way anova

Two questions of interest involving nonparametric multiple comparisons are considered. The first question concerns whether it is appropriate to use a multiple comparison procedure as a test of the equality of k treatments, and if it is, which procedure performs best as a test. Our results show that for smaller k values some multiple comparison procedures perform well as tests. The second question concerns whether a joint ranking or a separate ranking multiple comparison procedure performs better as a test and as a device for treatment separation. We find that the joint ranking procedure does slightly better as a test, but for treatment separation the answer depends on the situation.     

On (n-l)-wise and joint independence and normality of n Random variables: an example

An example is given of a vector of n random variables such that any (n-1)-dimensional subvector consists of n-1 independent standard normal variables. The whole vector however is neither independent nor normal.     

CO-tucker: a new method for the simultaneous analysis of a sequence of paired tables

Relationships between species and their environment are a key component to understand ecological communities. Usually, this kind of data are repeated over time or space for communities and their environment, which leads to a sequence of pairs of ecological tables, i.e. multi-way matrices. This work proposes a new method which is a combined approach of STATICO and Tucker3 techniques and deals to the problem of describing not only the stable part of the dynamics of structure–function relationships between communities and their environment (in different locations and/or at different times), but also the interactions and changes associated with the ecosystems’ dynamics. At the same time, emphasis is given to the comparison with the STATICO method on the same (real) data set, where advantages and drawbacks are explored and discussed. Thus, this study produces a general methodological framework and develops a new technique to facilitate the use of these practices by researchers. Furthermore, from this first approach with estuarine environmental data one of the major advantages of modeling ecological data sets with the CO-TUCKER model is the gain in interpretability.