An evaluation of ridge estimator in linear mixed models: an example from kidney failure data

This paper is concerned with the ridge estimation of fixed and random effects in the context of Henderson's mixed model equations in the linear mixed model. For this purpose, a penalized likelihood method is proposed. A linear combination of ridge estimator for fixed and random effects is compared to a linear combination of best linear unbiased estimator for fixed and random effects under the mean-square error (MSE) matrix criterion. Additionally, for choosing the biasing parameter, a method of MSE under the ridge estimator is given. A real data analysis is provided to illustrate the theoretical results and a simulation study is conducted to characterize the performance of ridge and best linear unbiased estimators approach in the linear mixed model.     

Should occupational codes be obtained from census data or from retrospective survey data in studies on occupational health?

The aim of this study was to assess the quality of occupational history information obtained via retrospective interview questions by comparison with occupational information for the same individuals obtained via a number of censuses. Moreover, morbidity patterns were investigated for different occupational exposure categories that were constructed either on occupational data gathered retrospectively or on data gathered longitudinally through censuses. The study population consisted of 6764 men and 2104 women who were interviewed within the Swedish Survey on Living Conditions. Census data on occupation from 1960, 1970 and 1975 were used for comparison. There was high level of agreement between the two data bases for occupational categories containing workers who were stable in their occupations. The correspondence was better for women. Prevalence rates for different long-term illnesses were almost the same for the categories, no matter which of the data bases was used for constructing the categories. Thus, we have found that self-reported work histories might be a useful way of controlling for occupational exposures in the past.     

Multiple input transfer function noise modelling in the time and frequency domain:empirical evidence from Monte Carlo simulations

In the present study we have evaluated two competing methods for estimation of the impulse response weights used in the identification of transfer function models:a time domain method involving biased regression techniques and a frequency domain method utilizing a discrete Fourier transform of the cross-covariance system of the transfer function model. The algorithms were implemented on a VAX-8800 computer at the Computing Center at Åbo Akademi. The evaluation of the competing methods was carried out by simulations of different transfer function noise model structures. The models are essentially the same as those of Edlund, but we have used a far greater number of replications in the cases tested. Furthermore, we have used actually identified and estimated autoregressive integrated moving-average models of the residuals in the identification procedure of impulse response weights, in contrast with Edlund who only used theoretical noise models in filtering the input and output series. After a shot discussion of the underlying theory, we present the procedures and results of the empirical testing.     

Bargaining over a finite set of alternatives

We analyze bilateral bargaining over a finite set of alternatives. We look for "good" ordinal solutions to such problems and show that Unanimity Compromise and Rational Compromise are the only bargaining rules that satisfy a basic set of properties. We then extend our analysis to admit problems with countably infinite alternatives. We show that, on this class, no bargaining rule choosing finite subsets of alternatives can be neutral. When rephrased in the utility framework of Nash (1950), this implies that there is no ordinal bargaining rule that is finite-valued. Professor Sertel passed away on January 25, 2003.     

A Randomized,Waiting-List-Controlled Study Shows That Brief,Mindfulness-Based Psychological Interventions Are Effective for Treatment of Women’s Low Sexual Desire

We evaluated two treatment conditions for low sexual desire in women: one where participants were administered a mindfulness-based treatment protocol and another with exercises focusing on scheduled sex and motivations for sex in addition to the aforementioned protocol. Seventy women (M_age 39.2, SD = 9.8) with complaints of low sexual desire were randomly allocated to one of these treatment conditions or a waiting-list condition. Participants attended four individual sessions and completed homework exercises. Questionnaire data were collected before and after treatment and at follow-ups three and six months later. Primary outcomes were the Female Sexual Function Index (FSFI) desire subdomain and the Sexual Interest and Desire Inventory–Female (SIDI-F). Secondary outcomes were the Female Sexual Distress Scale–Revised (FSDS-R), the Revised Dyadic Adjustment Scale (RDAS), the Perceived Relationship Quality Components Inventory (PRQC), and the Brief Symptom Inventory–18 (BSI-18). Women in both treatment conditions reported significantly higher sexual desire (FSFI desire d = 0.75 to 1.06) immediately following treatment, compared to the waiting list. Improvements were sustained at follow-up, accompanied by improvements in some secondary outcomes. We found no significant differences between the treatment conditions in terms of treatment effectiveness. Our study adds to the literature suggesting that mindfulness-based treatments are suitable options for treating low sexual desire in women.     

Minimal conversely consistent extension of the men-optimal solution

This study pertains to two-sided, one-to-one matching problems and considers the best-known solution concept: the men-optimal solution. The men-optimal solution fails to satisfy consistency as well as converse consistency. Furthermore, the minimal consistent extension of the men-optimal solution equals the core. In this article, we compute the minimal conversely consistent extension of the men-optimal solution as a correspondence which associates with each problem the set consisting of the men-optimal matching, and all stable and men-barterproof matchings for this problem.     

Linking Metatraits of the Big Five to Well-Being and Ill-Being: Do Basic Psychological Needs Matter?

There is considerable evidence that two higher order factors underlie the Big-Five dimensions and that these two factors provide a parsimonious taxonomy. However, not much empirical evidence has been documented as to the extent to which these traits relate to certain psychological constructs. In this study, we tested a structural model to investigate the individual differences in well-being and ill-being by examining the mediating effects of autonomy, relatedness, and competence on the extent to which two higher order factors of personality, namely Stability and Plasticity, are linked to life satisfaction and depression. In testing the model, we controlled for the effects of current affect. A large community sample participated and responded to self-measures of The Big-Five personality, basic psychological needs satisfaction, satisfaction with life, depressive symptoms, and positive and negative affect. The results revealed that satisfaction of basic psychological needs fully mediated the relationship between Plasticity and life satisfaction, as well as depression. It also fully mediated the relationship between Stability and life satisfaction, and partially mediated the relationship between Stability and depression.