Concomitant Information in Competing Risk Analysis

A competing risk model, accommodating both Type I censoring and random withdrawals, is expanded to incorporate concomitant information by allowing the parameters of the underlying distributions to be a linear function of two covariates. The model is developed for two competing risks, one following a Weibull distribution and the other a Rayleigh distribution, and random withdrawals following a Weibull distribution. A method is developed for testing the equality of the coefficients for a given covariate for each of the competing risks using MLE'.     

Multiattribute evaluation of regional cotton variety trials

Summary The Australian Cotton Cultivar Trials (ACCT) are designed to investigate various cotton [Gossypium hirsutum (L.)] lines in several locations in New South Wales and Queensland each year. If these lines are to be assessed by the simultaneous use of yield and lint quality data, then a multivariate technique applicable to three-way data is desirable. Two such techniques, the mixture maximum likelihood method of clustering and three-mode principal component analysis, are described and used to analyze these data. Applied together, the methods enhance each other's usefulness in interpreting the information on the line response patterns across the locations. The methods provide a good integration of the responses across environments of the entries for the different attributes in the trials. For instance, using yield as the sole criterion, the excellence of the namcala and coker group for quality is overlooked. The analyses point to a decision in favor of either high yields of moderate to good quality lint or moderate yield but superior lint quality. The decisions indicated by the methods confirmed the selections made by the plant breeders. The procedures provide a less subjective, relatively easy to apply and interpret analytical method of describing the patterns of performance and associations in complex multiattribute and multilocation trials. This should lead to more efficient selection among lines in such trials.     

To share or not to share: Incentivizing data sharing in life science communities

Most scientists recognize the importance of sharing data online in an open fashion. Nonetheless, many studies have documented the concerns that accompany data sharing activities, including loss of credit or IP, misuse and the time needed to curate interoperable data. To this end, discussions around data sharing often identify incentives that could potentially ameliorate these disincentivising concerns. Nonetheless, current Open Data discussions often rely on evidence‐based studies to identify the disincentives to overcome. This results in highly specific and directed interventions. In contrast, this paper offers a different interpretation of these concerns. To do so, it makes use of the Thomas Theorem which suggests that: “If men define situations as real, they are real in their consequences”. Using empirical evidence from sub‐Saharan African (bio)chemistry laboratories, this paper illustrates how individual perceptions of research environments – whether associated with evidence or not – are highly influential in shaping data sharing practices. It concludes with the suggestion that discussion on incentivising data sharing amongst scientific communities need to take a broader set of concerns into account and offer a more creative approach to ameliorating environmental disincentives.     

Interaction between atmospheric and pedospheric nitrogen nutrition in spruce (Picea abies L. Karst) seedlings

The effect of NO₂ fumigation on root N uptake and metabolism was investigated in 3-month-old spruce (Picea abics L. Karst) seedlings. In a first experiment, the contribution of NO₂ to the plant N budget was measured during a 48 h fumigation with 100mm³m^?3 NO₂. Plants were pre-treated with various nutrient solutions containing NO₂ and NH₄⁺, NO₃^? only or no nitrogen source for 1 week prior to the beginning of fumigation. Absence of NH₄⁺ in the solution for 6d led to an increased capacity for NO₃^? uptake, whereas the absence of both ions caused a decrease in the plant N concentration, with no change in NO₃^? uptake. In fumigated plants, NO₂ uptake accounted for 20–40% of NO₃^? uptake. Root NO₃^? uptake in plants supplied with NH₄⁺plus NO₃^? solutions was decreased by NO₂ fumigation, whereas it was not significantly altered in the other treatments. In a second experiment, spruce seedlings were grown on a solution containing both NO₂ and NH₄⁺ and were fumigated or not with 100mm³m^?3 NO₂ for 7 weeks. Fumigated plants accumulated less dry matter, especially in the roots. Fluxes of the two N species were estimated from their accumulations in shoots and roots, xylem exudate analysis and ¹⁵N labelling. Root NH₄⁺ uptake was approximately three times higher than NO₃^? uptake. Nitrogen dioxide uptake represented 10–15% of the total N budget of the plants. In control plants, N assimilation occurred mainly in the roots and organic nitrogen was the main form of N transported to the shoot. Phloem transport of organic nitrogen accounted for 17% of its xylem transport. In fumigated plants, neither NO₃^? nor NH₄⁺ accumulated in the shoot, showing that all the absorbed NO₂ was assimilated. Root NO₃^? reduction was reduced whereas organic nitrogen transport in the phloem increased by a factor of 3 in NO₂-fimugated as compared with control plants. The significance of the results for the regulation of whole-plant N utilization is discussed.     

Regression Models for Clinical Trials with Correlated Categorical Responses

Regression models for correlated categorical data are presented in which the covariance is a function of measured effects. The regression and covariance parameters are estimated by extended least square methods. A numerical example of a clinical trial comparing two antiemetic treatment regimes for patients receiving chemotherapy is given to illustrate the approach.     

Generalized Rank Transformations for Tests of Survival

The asymptotic equivalence of nonparametric tests and parametric tests based on rank-transformed data (CONOVER and IMAN , 1981) can be extended to the case of censoring. This paper presents generalized rank transformations for analyses of censored data, of interval-censored data and of survival data with uncertain causes of death. A Monte Carlo study and an analysis of leukemia remission times demonstrate excellent agreement of suggested procedures with GEHAN 'S (1965) and PRENTICE 'S (1978) tests.