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An objective Bayesian procedure for testing in the two way analysis of variance is proposed. In the classical methodology the main effects of the two factors and the interaction effect are formulated as linear contrasts between means of normal populations, and hypotheses of the existence of such effects are tested. In this paper, for the first time these hypotheses have been formulated as objective Bayesian model selection problems. Our development is under homoscedasticity and heteroscedasticity, providing exact solutions in both cases. Bayes factors are the key tool to choose between the models under comparison but for the usual default prior distributions they are not well defined. To avoid this difficulty Bayes factors for intrinsic priors are proposed and they are applied in this setting to test the existence of the main effects and the interaction effect. The method has been illustrated with an example and compared with the classical method. For this example, both approaches went in the same direction although the large P value for interaction (0.79) only prevents us against to reject the null, and the posterior probability of the null (0.95) was conclusive. [ABSTRACT FROM AUTHOR]

In animal digestibility the proportion of degraded food along the time has usually been modeled as a normal random variable with mean a function of the time and the following three parameters: the proportion of degraded food almost instantaneously, remaining proportion of food to be degraded, and velocity of degradation. The estimation of these parameters has been carried out mainly from a frequentist viewpoint by using the asymptotic distribution of the maximum likelihood estimator. This may give inadmissible estimates, such as values outside of the range of the parameters. This drawback could not appear if a Bayesian approach were adopted. In this article an objective Bayesian analysis is developed and illustrated on real and simulated data. [ABSTRACT FROM AUTHOR]

The study was conducted to assess time trend shifts of leading causes of death and their partial contributions over the years 1975–2016 in Spain. A longitudinal ecological epidemiologic design was conducted to analyse linear trend period shifts using joinpoint regression as the annual percentage of change (APC) in the period 1975–2016. The partial contributions were illustrated as the rate ratio of a singular-cause to their major-cause shift periods. HIV/AIDS shaped the increasing trend period of infectious diseases in 1989–1995 (APC = 25.3, P < 0.05) and the decreasing trend in 1995–1999 and 1999–2016. Lung cancer fell gradually from 1994 in men (−0.4, P < 0.05); however, in women, the condition continued increasing from 1990 (P < 0.05). Dementia types influenced mental and neurological disease drifts. The recent trend for circulatory periods (1980–2016) was mainly modulated by cardiac ischaemia, with increased partial contributions (25%, 32% and 30%). Traffic accidents defined the descending tendency of external causes. Spain showed a Western pattern in descended rates, including non-decreasing trends in mental and neurological diseases, pancreatic cancer, drug abuse and suicide. Trend shifts and partial contributions illustrated targets for further mortality reduction. Image 1 • The partial contributions of singular death causes allowed understanding mortality trends of their major causes of death. • Research on trend shifts of death causes is a toll for epidemiological surveillance and health policy tackling. • Mortality has been descending in Spain, except in mental and neurological diseases, and pancreatic cancer, drug abuse and suicide. [ABSTRACT FROM AUTHOR]