The Farm Crisis and Mental Health: A Longitudinal Study of the 1980s1

Abstract This paper examines rural/urban differences and trends in mental health during the farm crisis of the 1980s in a large panel sample from a midwestern state. A community research perspective, which attributes differences to life styles, culture, and community context, is contrasted with an economic stress perspective, which focuses on individual differences in economic circumstances as determinants of rural-urban differences in mental health. Survey samples from 1981, 1986, and 1989 are used to examine differences among seven categories of community type. Multiple regression analysis of the trend and panel data provide support for both the individual economic distress and community context models.     

TESTING SPHERICITY UNDER A MIXTURE MODEL

The robustness of Mauchly's sphericity test criterion when sampling from a mixture of two multivariate normal distributions is studied. The distribution of the sphericity test criterion when the sample covariance matrix has a non-central Wishart density of rank one is derived in terms of Meijer's G-functions; its distribution under the mixture model is then deduced. The robustness is studied by computing actual significance levels of the test under the mixture model using the critical values under the usual normal model.     

A note on inverse estimation in non-linear models

The problem of estimating the value of an x variable for a given proportion of an observed value of the y variable is consdered for a non-linear model. Asymptotic confidence limits are obtained and an application of the method is illustrated witreal data.     

MINING ERROR VARIANCE AND HITTING PAY-DIRT:

According to traditional error theory, sentiment measurements vary unsystematically from individual to individual. However, we find some patterned deviation in sentiments that characterize subsets of respondents within a seemingly homogeneous population. After demonstrating the existence of such patterns, we report an exploratory study aimed at identifying social characteristics of people with different patterns of sentiments. People embedded in multiple social networks have exaggerated sentiments that contour cultural patterns, and people with few social associations have attenuated sentiments conveying cultural detachment. In addition, people with disciplinary parents and romantic privation have some distinctive sentiments, depending on their gender.     

Estimation of noncentrality parameters

We propose some estimators of noncentrality parameters which improve upon usual unbiased estimators under quadratic loss. The distributions we consider are the noncentral chi-square and the noncentral F. However, we give more general results for the family of elliptically contoured distributions and propose a robust dominating estimator.     

Creating a reference to a complex emergency situation using time series methods: war in Guinea-Bissau 1998-1999

Impacts of complex emergencies or relief interventions have often been evaluated by absolute mortality compared to international standardized mortality rates. A better evaluation would be to compare with local baseline mortality of the affected populations. A projection of population-based survival data into time of emergency or intervention based on information from before the emergency may create a local baseline reference. We find a log-transformed Gaussian time series model where standard errors of the estimated rates are included in the variance to have the best forecasting capacity. However, if time-at-risk during the forecasted period is known then forecasting might be done using a Poisson time series model with overdispersion. Whatever, the standard error of the estimated rates must be included in the variance of the model either in an additive form in a Gaussian model or in a multiplicative form by overdispersion in a Poisson model. Data on which the forecasting is based must be modelled carefully concerning not only calendar-time trends but also periods with excessive frequency of events (epidemics) and seasonal variations to eliminate residual autocorrelation and to make a proper reference for comparison, reflecting changes over time during the emergency. Hence, when modelled properly it is possible to predict a reference to an emergency-affected population based on local conditions. We predicted childhood mortality during the war in Guinea-Bissau 1998-1999. We found an increased mortality in the first half-year of the war and a mortality corresponding to the expected one in the last half-year of the war.     

The Impact of Items and Anchors on Parent–Child Reports of Problem Behavior

Research has repeatedly demonstrated that parent and child reports of child behavior and emotional functioning often do not agree in terms of symptom severity or even symptom presence. Given the potential clinical impact that discrepant reports may have on the therapeutic process, a significant amount of research has addressed the factors influencing this observed discrepancy. Traditionally, this research has evaluated the impact of demographic factors on mean differences and obtained correlation coefficients between parent and child reports. The current research improves upon previous research in this area in two ways. First, the current research uses parent and child measures with identical rather than similar items as is commonly found in previous research. Second, the current research moves beyond identifying demographic influences on discrepant reports by explaining observed discrepancies in terms of differences in parent and child perceptions of typical child behavior.David Carlston and Benjamin Ogles are affiliated with Department of Psychology, Ohio University, Athens, USA.Funding for this project was provided by the Ohio Department of Mental Health.