Some Adaptive Robust Estimators which Work with Real Data

An adaptive R-estimator θ_A and an adaptive trimmed mean MAT are proposed. The performance of these and a number of other robust estimators are studied on real data sets, drawn from the astronomical, behavioural, biomedical, chemical, engineering and physical sciences. In the case of sets that can be assumed to have come from symmetric distributions, the best performer is θ_A. The next best performers are the Hodges-Lehmann estimator, Bisquare (7.5) and Huber (1.5), in that order. MAT works well with all kinds of sets–symmetric or skewed. Extensions of these results to ANOVA and regression models are mentioned.     

Antler and Body Weight Allometry in Red Deer: A Comparison of Statistical Estimators

In allometric expressions, both variables are measured with error. Such structural relationships require specific statistical techniques for precise and valid estimation of equation parameters. The relative growth pattern for antler weight and body weight was examined for 1700 red deer (Cervus elaphus L.) stags from the Harz mountain district in West Germany. Coefficients for the allometric equation were determined using several statistical estimation procedures and the results were compared and evaluated. There is evidence that the magnitude of the exponent in the allometric expression increases with the onset of sexual maturity.     

A Monte Carlo Study of Robustness of Pretest and Shrinkage Estimators in Pooling Coefficients of Variation

Pooling data, when justified, is advantageous for estimating the true parameter. In this paper the problem of estimating the coefficient of variation is considered when it is a priori suspected that two coefficients of variation are the same. Various estimators based on pretest and shrinkage rules are considered. A comparison through the Simulated Mean Squared Error (SMSE) criterion is carried out among various proposed estimators of the target coefficient of variation. The relative simulated efficiencies of the restricted, shrinkage restricted and shrinkage pretest estimators are studied. It is found that the proposed estimators are quite robust when the sample sizes are not too large. The result of Monte Carlo study indicates that the proposed shrinkage pretest estimator is efficient than the usual estimator in a wider range.     

Reconciling Genetic and Demographic Estimators of Effective Population Size in the Anuran Amphibian Bufo Calamita

We used genetic and demographic methods to estimate the variance effective population sizes (N _e) of three populations of natterjack toads Bufo calamita in Britain. This amphibian breeds in temporary pools where survival rates can vary among families. Census population sizes (N) were derived from spawn string counts. Point and coalescent-based maximum likelihood estimates of N _e based on microsatellite allele distributions were similar. N _e/N ratios based on genetic estimates of N _e ranged between 0.02 and 0.20. Mean demographic estimates of N _e were consistently higher (2.7–8.0-fold) than genetic estimates for all three populations when variance in breeding success was evaluated at the point where females no longer influence their progeny. However, discrepancies between genetic and demographic estimators could be removed by using a model that included extra variance in survivorship (above to Poisson expectations) among families. The implications of these results for the estimation of N _e in wild populations are discussed.     

Robust Joint Modeling of Longitudinal Measurements and Competing Risks Failure Time Data

Existing methods for joint modeling of longitudinal measurements and survival data can be highly influenced by outliers in the longitudinal outcome. We propose a joint model for analysis of longitudinal measurements and competing risks failure time data which is robust in the presence of outlying longitudinal observations during follow‐up. Our model consists of a linear mixed effects sub‐model for the longitudinal outcome and a proportional cause‐specific hazards frailty sub‐model for the competing risks data, linked together by latent random effects. Instead of the usual normality assumption for measurement errors in the linear mixed effects sub‐model, we adopt a t ‐distribution which has a longer tail and thus is more robust to outliers. We derive an EM algorithm for the maximum likelihood estimates of the parameters and estimate their standard errors using a profile likelihood method. The proposed method is evaluated by simulation studies and is applied to a scleroderma lung study (© 2009 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)     

H广义线性模型中的参数估计的比较

本文研究H广义线性模型中未知参数的两种估计方法,一种是边际似然函数法,另一种是Lee和Nelder提出来的L-N法．对于一类具有两个随机效应的典型的Poisson-Gamma类模型,在一些正则性条件之下,我们已经证明了其中固定效应卢的L-N估计的强相合性及渐近正态性,并得到了其收敛于真值的速度．针对这类模型,本文进一步给出了其边际似然函数的解析表达式,并且通过Monte Carlo模拟,对模型中固定效应β的边际似然估计和L—N估计进行了比较,模拟表明L—N估计比边际似然估计在拟Poisson-Gamma模型中有着更加优良的表现,具有更高的精度。     

Further Investigation on Naturally Occurring Tocopherols and Tocotrienols in Bovine Milk Fat

The polar lipid material which contains most of unsaponiriable matter of milk fat was collected by means of neutral alumina column chromatography. After saponification of the polar lipid material, the unsaponiriable matter was purified by repeated Florisil and neutral alumina column chromatography and the total tocopherol fraction was obtained. It was found that the total tocopherol fraction isolated from milk fat contained 6 of the known naturally occurring tocopherols, that is, α-, β-, γ-, and δ-tocopherols and α- and γ-tocotrienols. These were identified by two-dimensional thin-layer and gas-liquid chromatography before and after hydrogenation.     

An Improved Class of Estimators for Finite Population Mean in Sample Surveys

This paper proposes a class of estimators for estimating the finite population mean -Y of a study variate y using information on two auxiliary variates, one of which is positively and the other negatively correlated with the study variate y. An “asymptotically optimum estimator” (AOE) in the class is identified with its bias and mean square error formulae. It is observed that the proposed AOE is more efficient than Srivastava (1965), Srivastava (1974), Prasad (1989) and Gandge , Varghese , and Prabhu-Ajgaonkar (1993) estimators.     

Milk Collection in the Rat Using Capillary Tubes and Estimation of Milk Fat Content by Creamatocrit

Milk, as the sole source of nutrition for the newborn mammal, provides the necessary nutrients and energy for offspring growth and development. It also contains a vast number of bioactive compounds that greatly affect the development of the neonate. The analysis of milk components will help elucidate key factors that link maternal metabolism and health with offspring growth and development. The laboratory rat represents a popular model organism for maternal studies, and rat milk can be used to examine the effect of various maternal physiological, nutritional, and pharmacological interventions on milk components, which may then impact offspring health. Here a simple method of manually collecting milk from the lactating rat that can be performed by a single investigator, does not require specialized vacuum or suction equipment, and provides sufficient milk for subsequent downstream analysis is described. A method for estimating the fat content of milk by measuring the percentage of cream within the milk sample, known as the creamatocrit, is also presented. These methods can ultimately be used to increase insight into maternal-child health and to elucidate maternal factors that are involved in proper growth and development of offspring.     

Robust Estimation of Area Under ROC Curve Using Auxiliary Variables in the Presence of Missing Biomarker Values

Summary In medical research, the receiver operating characteristic (ROC) curves can be used to evaluate the performance of biomarkers for diagnosing diseases or predicting the risk of developing a disease in the future. The area under the ROC curve (ROC AUC), as a summary measure of ROC curves, is widely utilized, especially when comparing multiple ROC curves. In observational studies, the estimation of the AUC is often complicated by the presence of missing biomarker values, which means that the existing estimators of the AUC are potentially biased. In this article, we develop robust statistical methods for estimating the ROC AUC and the proposed methods use information from auxiliary variables that are potentially predictive of the missingness of the biomarkers or the missing biomarker values. We are particularly interested in auxiliary variables that are predictive of the missing biomarker values. In the case of missing at random (MAR), that is, missingness of biomarker values only depends on the observed data, our estimators have the attractive feature of being consistent if one correctly specifies, conditional on auxiliary variables and disease status, either the model for the probabilities of being missing or the model for the biomarker values. In the case of missing not at random (MNAR), that is, missingness may depend on the unobserved biomarker values, we propose a sensitivity analysis to assess the impact of MNAR on the estimation of the ROC AUC. The asymptotic properties of the proposed estimators are studied and their finite‐sample behaviors are evaluated in simulation studies. The methods are further illustrated using data from a study of maternal depression during pregnancy.     

Isolation and Characterization of Full and Truncated Forms of Human Breast Carcinoma Protein BA46 from Human Milk Fat Globule Membranes

We have isolated and characterized two proteins of 50 and 30 kDa from human milk fat globule membranes of healthy donors. N-terminal and internal sequencing revealed that the 50-kDa protein is the full-length human breast carcinoma protein BA46 that is highly expressed in human breast tumors. The 30-kDa protein is a truncated form of protein BA46 which consists of the C-terminal factor V/VIII-like domain of BA46 and which appears to anchor BA46 to the milk fat globule membrane. Defective release of the epidermal growth factor domain containing a surface RGD motif may be related to involvement of BA46 in breast cancer     

A Comparison of Robust Estimators in the Presence of Arbitrarily Right Censored Data

Robust estimation of a location parameter is considered when the data from an unknown symmetric population are subject to arbitrary right-censorship. Comparisons are made between various M-estimators, several L-estimators (trimmed means), and the Kaplan-Meier median. Ten sampling distributions, two uniform censoring distributions, and three sample sizes are examined. A Cauchy censoring distribution is also considered when the sample size is equal to twenty for each of the ten sampling distributions. Performance is based on the estimated mean square error.     

哺乳动物乳蛋白基因的表达与调控

本文在介绍了乳蛋白基因组结构及进化关系的基础上,就其乳蛋白基因表达的影响因素：顺式调控成分,反式作用因子及激素对表达的诱导进行了讨论,最后就该系统作为生物反应器的开发前景作了展望。     

Influence of Dietary Carbohydrate,Fat, and Protein on Lipogenesis in Rats

The incorporation of ¹⁴C of acetate-1-¹⁴C into the lipids of the liver and carcass, and the changes in the concentrations of nucleotides and citric acid in the liver were studied in the rats fed individual nutrients; starch, casein or corn oil. And the metabolism of citric acid-1,5-¹⁴C was also investigated after the feeding of nutrients. Lipogenesis in the liver and carcass was more markedly stimulated with starch than with casein or corn oil. In the liver of rats fed starch, the concentration of ATP doubled and that of citric acid was one-half of those with casein or corn oil, respectively. And the conversion of citric acid to carbon dioxide and lipids was stimulated with starch.