Correcting missing-data bias in historical demography

Studies on population history are often based on incomplete records of life histories. For instance, in studies using data obtained from family reconstitution, the date of death is right censored (by migration) and the censoring time is never observed. Several methods for the correction of mortality estimates are proposed in the literature, most of which first estimate the number of individuals at risk and then use standard techniques to estimate mortality. Other methods are based on statistical models. In this paper all methods are reviewed, and their merits are compared by applying them to simulated and to seventeenth-century data from the English parish of Reigate. An ad hoc method proposed by Ruggles performs reasonably well. Methods based on statistical models, provided they are sufficiently realistic, give comparable accuracy and allow the estimation of several other quantities of interest, such as the distribution of migration times.     

Homogamy by education and migration status in Monterrey,Mexico: changes and continuities over time

This paper reviews changes in homogamy by migration status and educational level in Monterrey, Mexico, through the analysis of marriage patterns for two cohorts of men born in 1905–1934 and 1940–1969. Results show a significant increase in educational homogamy, as well as in homogamy by rural origins. The changes suggest that education has played an increasingly important role in the process of mate selection, although certain particularistic characteristics, such as being a rural immigrant, are still important in marriage formation. The paper concludes with a discussion of the implications of these findings for the relationship between homogamy and social stratification.

Emotion Regulation in Low-income Preschoolers

The present study was concerned with identifying the causes of low-income preschoolers' negative emotions and their most common regulation responses. The relations of family socialization practices and temperament to the children's emotion regulation skills were also examined. Ninety predominantly minority low-income preschoolers (46 boys) and their mothers participated. During visits to the children's preschools, observers watched for expressions of anger and sadness, and recorded the causes of the displays and the children's reactions. Mothers reported on their emotion socialization and discipline practices and their children's temperament. Although the children expressed more anger than sadness, they used more constructive reactions in response to sadness and more non-constructive reactions in response to anger. Maternal reports of appropriate family emotion were associated with low levels of non-constructive regulation responses to anger and sadness whereas reports of inconsistent parental discipline were generally associated with non-constructive regulation responses. All in all, the findings of this study are in accord with findings on middle-income children and indicate that low- and middle-income children are more alike than different with regard to the regulation of negative emotion in the peer environment.     

Designing and integrating composite networks for monitoring multivariate gaussian pollution fields

Networks of ambient monitoring stations are used to monitor environmental pollution fields such as those for acid rain and air pollution. Such stations provide regular measurements of pollutant concentrations. The networks are established for a variety of purposes at various times so often several stations measuring different subsets of pollutant concentrations can be found in compact geographical regions. The problem of statistically combining these disparate information sources into a single 'network' then arises. Capitalizing on the efficiencies so achieved can then lead to the secondary problem of extending this network. The subject of this paper is a set of 31 air pollution monitoring stations in southern Ontario. Each of these regularly measures a particular subset of ionic sulphate, sulphite, nitrite and ozone. However, this subset varies from station to station. For example only two stations measure all four. Some measure just one. We describe a Bayesian framework for integrating the measurements of these stations to yield a spatial predictive distribution for unmonitored sites and unmeasured concentrations at existing stations. Furthermore we show how this network can be extended by using an entropy maximization criterion. The methods assume that the multivariate response field being measured has a joint Gaussian distribution conditional on its mean and covariance function. A conjugate prior is used for these parameters, some of its hyperparameters being fitted empirically.     

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.     

Importance of interpolation when constructing double-bootstrap confidence intervals

We show that, in the context of double-bootstrap confidence intervals, linear interpolation at the second level of the double bootstrap can reduce the simulation error component of coverage error by an order of magnitude. Intervals that are indistinguishable in terms of coverage error with theoretical, infinite simulation, double-bootstrap confidence intervals may be obtained at substantially less computational expense than by using the standard Monte Carlo approximation method. The intervals retain the simplicity of uniform bootstrap sampling and require no special analysis or computational techniques. Interpolation at the first level of the double bootstrap is shown to have a relatively minor effect on the simulation error.     

Confidence intervals for secondary parameters following a sequential test

In sequential studies, formal interim analyses are usually restricted to a consideration of a single null hypothesis concerning a single parameter of interest. Valid frequentist methods of hypothesis testing and of point and interval estimation for the primary parameter have already been devised for use at the end of such a study. However, the completed data set may warrant a more detailed analysis, involving the estimation of parameters corresponding to effects that were not used to determine when to stop, and yet correlated with those that were. This paper describes methods for setting confidence intervals for secondary parameters in a way which provides the correct coverage probability in repeated frequentist realizations of the sequential design used. The method assumes that information accumulates on the primary and secondary parameters at proportional rates. This requirement will be valid in many potential applications, but only in limited situations in survival analysis.     

Maternal Postpartum Depression Increases Vulnerability for Toddler Behavior Problems through Infant Cortisol Reactivity

The current study examined the role of hypothalamic‐pituitary‐adrenal reactivity (a physiological indicator of stress) in early infancy as a mediator of the relationship between maternal postpartum depression and toddler behavior problems. Participants were 137 at‐risk mothers and their children participating in a longitudinal study of intergenerational transmission of risk. Mothers’ depression was measured five times during the infants’ first 18 months. Infant cortisol was collected during a social stressor (the still‐face paradigm) when infants were 6 months old, and mothers reported on toddlers’ internalizing and externalizing symptoms at 18 months. Among this sample of high‐risk mother–infant dyads, early postpartum depression predicted atypical infant cortisol reactivity at 6 months, which mediated the effect of maternal depression on increased toddler behavior problems. Clinical implications are discussed.     

Too Hard to Shout Over the Loudest Frame: Effects of Competing Frames in the Context of the Crystallized Media Coverage on Offshore Outsourcing

This study investigates the effects of competing frames in newspaper coverage of offshore outsourcing, an issue that is characterized by a predominantly negative, unemployment-focused media framing. The findings of a randomized, controlled experiment (N = 152) demonstrate that conventional framing effects do hold for this issue and for this media context by moving recipients’ attitudes in the direction consistent with the valence of the frame. However, they also show the backfire effect of the positively valenced frame among recipients with greater interest in political and economic news, who become less supportive of outsourcing if they read a story framing outsourcing from a consumer-oriented perspective. Our results contribute to the ongoing debate about the limits of framing effects on forming opinion about contentious policy issues and demonstrate the challenges for nondominant perspectives to make their way to news-savvy audiences even when the nature of the issue in question necessitates considering them.