Application of pattern-mixture models to outcomes that are potentially missing not at random using pseudo maximum likelihood estimation

In this work, we fit pattern-mixture models to data sets with responses that are potentially missing not at random (MNAR, Little and Rubin, 1987). In estimating the regression parameters that are identifiable, we use the pseudo maximum likelihood method based on exponential families. This procedure provides consistent estimators when the mean structure is correctly specified for each pattern, with further information on the variance structure giving an efficient estimator. The proposed method can be used to handle a variety of continuous and discrete outcomes. A test built on this approach is also developed for model simplification in order to improve efficiency. Simulations are carried out to compare the proposed estimation procedure with other methods. In combination with sensitivity analysis, our approach can be used to fit parsimonious semi-parametric pattern-mixture models to outcomes that are potentially MNAR. We apply the proposed method to an epidemiologic cohort study to examine cognition decline among elderly.     

Robust estimation of multivariate covariance components

In many settings, such as interlaboratory testing, small area estimation in sample surveys, and heritability studies, investigators are interested in estimating covariance components for multivariate measurements. However, the presence of outliers can seriously distort estimates obtained using standard procedures such as maximum likelihood. We propose a procedure based on M-estimation for robustly estimating multivariate covariance components in the presence of outliers; the procedure applies to balanced and unbalanced data. We present an algorithm for computing the robust estimates and examine the performance of the estimator through a simulation study. The estimator is used to find covariance components and identify outliers in a study of variability of egg length and breadth measurements of American coots.     

Microsatellite analysis of genetic variation in black bear populations

Measuring levels of genetic variation is an important aspect of conservation genetics The informativeness of such measurements is related to the variability of the genetic markers used; a particular concern in species, such as bears, which are characterized by low levels of genetic variation resulting from low population densities and small effective population sizes We describe the development of microsatellite analysis in bears and its use in assessing interpopulation differences in genetic variation in black bears from three Canadian National Parks These markers are highly variable and allowed identification of dramatic differences in both distribution and amount of variation between populations Low levels of variation were observed in a population from the Island of Newfoundland The significance of interpopulation differences in variability was tested using a likelihood ratio test of estimates of θ= 4 N_eu.     

Homozygosity and Heterozygosity in three Populations of Rivulus marmoratus

Rivulus marmoratus is a self-fertilizing hermaphroditic fish found in the tropical Atlantic as populations of homozygous clones, with the exception of a single site in Belize where male fish are abundant and heterozygosity is the norm. The presence of male fish apparently leads to outcrossing and heterozygosity, but males have been found in limited numbers in other populations which are homozygous. DNA fingerprinting now reveals that the Belize population has remained heterozygous, with a high proportion of males (20–25%), for several years. In addition, two newly discovered populations with a lower percentage of males (1–2%) are reported from the Bahamas and Honduras. One of these populations (Bahamas) consists of homozygous clones, while the other (Honduras) displays a limited proportion of heterozygosity. The Honduras population is only the second outcrossing population known in this species, and the limited heterozygosity seen here may reflect the lower proportion of males.     

DNA fingerprinting in clonal organisms

The use of DNA fingerprinting to identify members of the same clone in completely or partially asexual organisms requires that the individuals within a clone share a recent common ancestor. By considering the expected distributions of band–sharing values in asexual and sexual organisms, it is shown that DNA fingerprinting may be effective in distinguishing members of the same clone, provided that the frequency of sexual reproduction is considerably greater than the minisatellite mutation rate.