Jornal de Biometria e Bioestatística

A comparison among two forms of half-diallel analysis was made. The different half-diallel techniques used were: Griffing\\\'s model I, method 2 and 4. These methods of diallel analysis were found to be interrelated. However, as the Griffing\\\'s model I, method 4 model partitioned heterosis into different components as well as gave information about combining ability and this method had certainly some advantages over the other. The results further indicated the using parental generations in the second Griffing method may cause biased estimate of the GCA and SCA variances. Thus, using the fourth Griffing method is more suitable than the other methods in providing time, cost and facilities, and is recommended as an applicable method.

A k-order generalization of the linear diagonals-parameter symmetry model is proposed, and related orthogonal decompositions of the generalization are inspected. Applications to randomized clinical trials are given.

In a population practicing consanguineous marriage, rare recessive lethal alleles (RRLA) have higher chances of affecting phenotypes. As inbreeding causes more homozygosity and subsequently more deaths, the loss of individuals with RRLA decreases the frequency of these alleles. Although this phenomenon is well studied in general, here some hitherto unstudied cases are presented. An analytical formula for the RRLA frequency is presented for infinite monoecious population practicing several different types of inbreeding. In finite diecious populations, it is found that more severe inbreeding leads to quicker RRLA losses, making the upcoming generations healthier. A population of size 10,000 practicing 30% half-sib marriages loses more than 95% of its RRLA in 100 generations; a population practicing 30% cousin marriages loses about 75% of its RRLA. Our findings also suggest that given enough resources to grow, a small inbred population will be able to rebound while losing the RRLA.

Heritability estimates a polygenic effect on a trait for a population. Reliable interpretation of heritability is critical in planning further genetic studies to locate a gene responsible for the trait. This study accommodates both single and multiple trait cases by employing regression models for correlation parameter to infer the heritability. Sharing the properties of regression approach, the proposed methods are exible to incorporate non-genetic and/or non-additive genetic information in the analysis. The performances of the proposed model are compared with those using the likelihood approach through simulations and carotid Intima Media Thickness analysis from Northern Manhattan family Study.

Fingerprints have been the gold standard for personal identification within the forensic community for more than one hundred years. Fingerprints and finger marks combine to provide the most powerful means of personal identification available to police and courts. The basic patterns of fingerprints are loops, whorls and arches that can be found in fingerprints. The standard methodology used by fingerprint experts to conduct friction ridge examinations is called ACE-V, for analysis, comparison, evaluation, and verification, which are the four fundamental phases utilized in this process. The recovered prints can be manually compared with known antemortem records or searched through an automated fingerprint system (AFIS) in order to verify or establish identity.

Low birthweight (LBW) is a well-known risk factor for infant mortality worldwide. Although infant mortality has decreased in the United States during the past 20 years, the incidence of LBW has increased, suggesting that further reductions in infant mortality may be possible if the incidence of LBW can be reduced. In the present work, we introduce a new analytic framework for revealing the relationships between latent variables representing components in a mixture model for birthweight distribution and various other risk factors. More specifically, we show how to estimate the probability that a risk factor is present within one of the mixture components as well as the probability of mixture component membership among infants for whom a risk factor is present, both at a fixed birthweight and averaged across birthweights. We illustrate our analytic framework using publicly available data for white singletons born in the United States between 1998 and 2002. This framework provides a quantitative approach for the prediction of how addressing a modifiable risk factor may affect both the incidence of LBW and infant mortality, thereby facilitating decision making regarding resource allocation toward addressing that risk factor.