Small area estimation: the EBLUP estimator based on spatially correlated random area effects

Small area estimation, Spatial correlation, SAR model, Spatial EBLUP, Lattice data,

Sampling designs on stream networks using the pseudo-Bayesian approach

Monitoring stream networks through time provides important ecological information. The sampling design problem is to choose locations where measurements are taken so as to maximise information gathered about physicochemical and biological variables on the stream network. This paper uses a pseudo-Bayesian approach, averaging a utility function over a prior distribution, in finding a design which maximizes the average utility. We use models for correlations of observations on the stream network that are based on stream network distances and described by moving average error models. Utility functions used reflect the needs of the experimenter, such as prediction of location values or estimation of parameters. We propose an algorithmic approach to design with the mean utility of a design estimated using Monte Carlo techniques and an exchange algorithm to search for optimal sampling designs. In particular we focus on the problem of finding an optimal design from a set of fixed designs and finding an optimal subset of a given set of sampling locations. As there are many different variables to measure, such as chemical, physical and biological measurements at each location, designs are derived from models based on different types of response variables: continuous, counts and proportions. We apply the methodology to a synthetic example and the Lake Eacham stream network on the Atherton Tablelands in Queensland, Australia. We show that the optimal designs depend very much on the choice of utility function, varying from space filling to clustered designs and mixtures of these, but given the utility function, designs are relatively robust to the type of response variable

Application of approximate variances of variance components and their ratios in genetic tests

The application and underlying assumptions of formulae used to estimate the variance of variance components and ratios of variance components are fully described for (1) variance components estimated using Henderson's Method 3 (HM3) and Restricted Maximum Likelihood (REML) and (2) ratios of variance components commonly used in genetic tests - biased and unbiased heritabilities. A first-order Taylor series approximation is often used to estimate the variance of a ratio of two random variables (e.g., heritability), however the formula is complicated, thus making calculations prone to errors. Dickerson's approximation is considerably simpler, though relatively rarely used. In case studies using data from 148 slash pine full-sib progeny tests, Dickerson's method was found to be slightly more conservative than the Taylor series approximation when estimating the variance of heritability estimates, regardless of test size, age, or the trait (volume, which is a continuous trait, and rust resistance, which is a bernoulli trait). Both the Taylor series and Dickerson approximations compared favorably with an empirical estimate of the variance of heritability estimates, however there is some evidence of small-sample bias associated with the use of the asymptotic variance-covariances from REML variance component estimation. © 1995 Springer-Verlag

Impact of maternal and paternal preconception health on birth outcomes using prospective couples’ data in Add Health

PURPOSE: Retrospective studies of preconception health have demonstrated that parents’ health conditions and behaviors can impact a newborn’s birth outcomes and, subsequently, future health status. This study sought to examine the impact of preconception health, measured prospectively, among both mothers and fathers, on two important birth outcomes: birthweight and gestational age. METHODS: Data came from Add Health (the National Longitudinal Study of Adolescent Health), which included interviews with original participants and a subsample of their partners in 2001–02. In 2008, the original respondents again completed an interview for Add Health. For 372 eligible infants born to these couples, birth outcomes (measured in 2008) were regressed on preconception health conditions and behaviors among non-pregnant heterosexual partners (measured in 2001–02). RESULTS: Mean birthweight was 3399 grams, and mean gestational age was 39 weeks. Birthweight was higher for infants born to mothers with diabetes or high blood pressure, and for mothers who drank alcohol at least once per month, and lower for infants born to fathers with diabetes (p < .05). Infant gestational age was marginally lower for infants born to mothers with higher levels of depression (p < .10), and lower for infants born to fathers with diabetes and with higher levels of fast food consumption (p < .05). CONCLUSIONS: Both maternal and paternal preconception health conditions and behaviors influenced infant birth outcomes. Interventions to promote preconception health should focus on prevention of diabetes and high blood pressure, as well as minimizing consumption of alcohol and fast food