background and aims: diabetes type ii (non-insulin dependent) which is one of the most prevalent diabetes types in the world emerges in people with the age of above 55 and genetic and environmental factors interfere in this disease. the aim of this study was to determine the factors affecting diabetes type ii with generalized mixed linear model. methods: population of this study included 2820 p...

A pig changes over time: it puts on weight and eats more, as it becomes larger. Different pigs grow in a different manner. There is evidence that these differences in growth patterns between pigs are caused by genetic factors. This gives the opportunity to select for these different growth patterns, to better meet the demands of markets that differ in desired slaughter weight, eg Bacon, fresh p...

Random coefficient regressions have been applied in a wide range of fields, from biology to economics, and constitute a common frame for several important statistical models. A nonparametric approach to inference in random coefficient models was initiated by Beran and Hall. In this paper we introduce and study goodness of fit tests for the coefficient distributions; their asymptotic behaviour u...

The objectives of this study were to estimate genetic parameters for egg production over the age trajectory in 3 layer lines, which represent different biotypes for egg production, and to validate the use of breeding values for slope as a measure of persistency to be used in the selection program. Egg production of more than 26,000 layers per line from 6 consecutive generations were analyzed wi...

A procedure for obtaining approximate reliabilities of estimated breeding values under a random regression model is presented. The method is based on a concept of an equivalent number of progeny, with subsequent selection index approximation of reliability utilising equivalent progeny information on the animal and its parents. The accuracy of the proposed approximation was tested using a multip...

one of the models that can be used to study the relationship between boolean random sets and explanatory variables is growth regression model which is defined by generalization of boolean model and permitting its grains distribution to be dependent on the values of explanatory variables. this model can be used in the study of behavior of boolean random sets when their coverage regions variation...

AMS subject classifications: 62H12 62G20 Keywords: Covariates missing at random Inverse selection probability Multi-index model Single-index model a b s t r a c t This paper considers estimation of the semiparametric multi-index model with missing covariates at random. A weighted estimating equation is suggested by invoking the inverse selection probability approach, and estimators of the indic...

Data, collected to model risk of an interesting event, often have a multilevel structure as patients are clustered within larger units, e.g. clinical centers. Risk of the event is usually modeled using a logistic regression model, with a random intercept to control for heterogeneity among clusters. Model specification requires to decide which regressors have a non-negligible effect, and hence, ...

Properties of random regression models using linear splines (RRMS) were evaluated with respect to scale of parameters, numerical properties, changes in variances and strategies to select the number and positions of knots. Parameters in RRMS are similar to those in multiple trait models with traits corresponding to points at knots. RRMS have good numerical properties because of generally superio...