Continuous outcomes stochastically mismeasured as discrete random variables: a maximum likelihood approach

In an economic model of retirement behavior, a continuous dependent variable was required; the variable could only be estimated discretely with error, however. Parameter estimates using this dependent variable and ordinary least squares regression are inefficient. In th is paper, we develop a maximum likelihood procedure which adjusts for this heteroscedasticity.     

A frequency domain comparison of estimation methods for gaussian fields

This paper demonstrates that well-known parameter estimation methods for Gaussian fields place different emphasis on the high and low frequency components of the data. As a consequence, the relative importance of the frequencies under the objective of the analysis should be taken into account when selecting an estimation method, in addition to other considerations such as statistical and computational efficiency. The paper also shows that when noise is added to the Gaussian field, maximum pseudolikelihood automatically sets the smoothing parameter of the model equal to one. A simulation study then indicates that generalised cross-validation is more robust than maximum likelihood un-

der model misspecification in smoothing and image restoration problems. This has implications for Bayesian procedures since these use the same weightings of the frequencies as the likelihood.     

Bayesian prediction of waiting times in stochastic models

The authors show how saddlepoint techniques lead to highly accurate approximations for Bayesian predictive densities and cumulative distribution functions in stochastic model settings where the prior is tractable, but not necessarily the likelihood or the predictand distribution. They consider more specifically models involving predictions associated with waiting times for semi‐Markov processes whose distributions are indexed by an unknown parameter θ. Bayesian prediction for such processes when they are not stationary is also addressed and the inverse‐Gaussian based saddlepoint approximation of Wood, Booth & Butler (1993) is shown to accurately deal with the nonstationarity whereas the normal‐based Lugannani & Rice (1980) approximation cannot, Their methods are illustrated by predicting various waiting times associated with M/M/q and M/G/1 queues. They also discuss modifications to the matrix renewal theory needed for computing the moment generating functions that are used in the saddlepoint methods.     

Identity,difference and community in Southern Irish Protestantism: The Protestants of West Cork

This article looks at how the Protestants of West Cork came to terms with Irish independence, and how they have responded to the major social and political changes of the past decades. West Cork Protestants are geographically peripheral to the Southern Protestant population as a whole, and have a weaker socio-economic profile. They live in an area that saw some of the fiercest fighting and worst atrocities in the war of independence and civil war. Their experience throws considerable light on issues of whether Protestants were a privileged or oppressed minority, and whether and how they integrated into the new state. Extensive in-depth interviews are used to show how West Cork Protestants reconstructed their identity, defined their differences from Catholics and maintained community in the years since independence.     

Biased Bootstrap Methods for Reducing the Effects of Contamination

Contamination of a sampled distribution, for example by a heavy-tailed distribution, can degrade the performance of a statistical estimator. We suggest a general approach to alleviating this problem, using a version of the weighted bootstrap. The idea is to 'tilt' away from the contaminated distribution by a given (but arbitrary) amount, in a direction that minimizes a measure of the new distribution's dispersion. This theoretical proposal has a simple empirical version, which results in each data value being assigned a weight according to an assessment of its influence on dispersion. Importantly, distance can be measured directly in terms of the likely level of contamination, without reference to an empirical measure of scale. This makes the procedure particularly attractive for use in multivariate problems. It has several forms, depending on the definitions taken for dispersion and for distance between distributions. Examples of dispersion measures include variance and generalizations based on high order moments. Practicable measures of the distance between distributions may be based on power divergence, which includes Hellinger and Kullback–Leibler distances. The resulting location estimator has a smooth, redescending influence curve and appears to avoid computational difficulties that are typically associated with redescending estimators. Its breakdown point can be located at any desired value ε∈ (0, ½) simply by 'trimming' to a known distance (depending only on ε and the choice of distance measure) from the empirical distribution. The estimator has an affine equivariant multivariate form. Further, the general method is applicable to a range of statistical problems, including regression.     

Leadership of highly creative people in highly creative fields: A historiometric study of scientific leaders

In recent years there has been a marked increase in the study of the influence of leadership on creativity, and the effects of this relationship on organizational performance. While a number of explanations have been broached with regard to the positive effects of leadership on creativity, many of these studies propose different, and often contradictory, methods for leaders to achieve these positive effects on creativity within their organizations and work groups. Additionally, little work has been done examining the effects of leadership on highly creative people in fields requiring creativity. The purpose of this study is to examine two existing leadership theories with regard to their viability as models to explain creative performance of eminent scientists. Eminent scientists represent a population of leaders of highly creative individuals in a field that values the production of innovative ideas and products as a marker of performance. Ninety-three excerpts from the biographies of scientists were content coded for leader behaviors and performance criteria. The results of this analysis indicate that a model based on strategic planning and product championing may serve to explain the positive effects of leadership on creativity in a highly creative population.     

The critique of intelligent design: Epicurus,Marx, Darwin,and Freud and the materialist defense of science

A new version of the age-old controversy between religion and science has been launched by today’s intelligent design movement. Although ostensibly concerned simply with combating Darwinism, this new creationism seeks to drive a “wedge” into the materialist view of the world, originating with the ancient Greek philosopher Epicurus and manifested in modern times by Darwin, Marx, and Freud. Intelligent design proponents thus can be seen as challenging not only natural and physical science but social science as well. In this article, we attempt to explain the long history of this controversy, stretching over millennia, and to defend science (especially social science) against the criticisms of intelligent design proponents – by defending science’s materialist roots.

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Income Inequality across the Rural-Urban Continuum in the United States, 1970–2016*

The growth in macro-level income inequality in the United States is well established, but less is known about patterns of inequality at subnational scales and how they vary between and within rural and urban localities. Using data from the Decennial Census and American Community Survey, we produce estimates of within-county income inequality from 1970 to 2016 and analyze differences in inequality levels, the persistence of high (low) inequality, and populations' exposure to high (low) inequality across the rural-urban continuum. We find that income inequality has historically been higher in non-metropolitan than metropolitan counties, but inequality levels converged by 2016 due to growing inequality in metropolitan counties. Additionally, levels of inequality were generally persistent within counties over time, except that counties characterized by low inequality in 1970 were unlikely to remain as such in 2016. Third, non-trivial shares of the metropolitan population resided in low-inequality contexts in 1970, but virtually none of the U.S. population resided in such places by 2016. Residence in high-inequality counties is normative in rural and urban America. This statistical analysis provides an updated portrait of income inequality across the rural-urban continuum, and should spur additional research on stratification in rural America during an era of growing inequality.