A modified false discovery rate multiple-comparisons procedure for discrete data, applied to human immunodeficiency virus genetics

Summary.  To help to design vaccines for acquired immune deficiency syndrome that protect broadly against many genetic variants of the human immunodeficiency virus, the mutation rates at 118 positions in HIV amino-acid sequences of subtype C versus those of subtype B were compared. The false discovery rate (FDR) multiple-comparisons procedure can be used to determine statistical significance. When the test statistics have discrete distributions, the FDR procedure can be made more powerful by a simple modification. The paper develops a modified FDR procedure for discrete data and applies it to the human immunodeficiency virus data. The new procedure detects 15 positions with significantly different mutation rates compared with 11 that are detected by the original FDR method. Simulations delineate conditions under which the modified FDR procedure confers large gains in power over the original technique. In general FDR adjustment methods can be improved for discrete data by incorporating the modification proposed.     

Immigrants' Language Skills and Visa Category1

This article is concerned with the determinants of English language proficiency among immigrants in a longitudinal survey for Australia. It focuses on both visa category and variables derived from an economic model of the determinants of destination‐language proficiency among immigrants. Skills‐tested and economic immigrants have the greatest proficiency shortly after immigration, followed by family‐based visa recipients, with refugees having the lowest proficiency. Other variables the same, these differences disappear by 3.5 years after immigration for speaking skills; and although they diminish, they persist longer for reading and writing skills. The variables generated from the model of destination‐language proficiency (such as schooling and age at migration) are, in part, predictions of visa category, but they are more important statistically for explaining proficiency.     

Exposure Reconstruction for the TCDD-Exposed NIOSH Cohort Using a Concentration- and Age-Dependent Model of Elimination

Recent studies demonstrating a concentration dependence of elimination of 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD) suggest that previous estimates of exposure for occupationally exposed cohorts may have underestimated actual exposure, resulting in a potential overestimate of the carcinogenic potency of TCDD in humans based on the mortality data for these cohorts. Using a database on U.S. chemical manufacturing workers potentially exposed to TCDD compiled by the National Institute for Occupational Safety and Health (NIOSH), we evaluated the impact of using a concentration- and age-dependent elimination model (CADM) (Aylward et al., 2005) on estimates of serum lipid area under the curve (AUC) for the NIOSH cohort. These data were used previously by Steenland et al. (2001) in combination with a first-order elimination model with an 8.7-year half-life to estimate cumulative serum lipid concentration (equivalent to AUC) for these workers for use in cancer dose-response assessment. Serum lipid TCDD measurements taken in 1988 for a subset of the cohort were combined with the NIOSH job exposure matrix and work histories to estimate dose rates per unit of exposure score. We evaluated the effect of choices in regression model (regression on untransformed vs. ln-transformed data and inclusion of a nonzero regression intercept) as well as the impact of choices of elimination models and parameters on estimated AUCs for the cohort. Central estimates for dose rate parameters derived from the serum-sampled subcohort were applied with the elimination models to time-specific exposure scores for the entire cohort to generate AUC estimates for all cohort members. Use of the CADM resulted in improved model fits to the serum sampling data compared to the first-order models. Dose rates varied by a factor of 50 among different combinations of elimination model, parameter sets, and regression models. Use of a CADM results in increases of up to five-fold in AUC estimates for the more highly exposed members of the cohort compared to estimates obtained using the first-order model with 8.7-year half-life. This degree of variation in the AUC estimates for this cohort would affect substantially the cancer potency estimates derived from the mortality data from this cohort. Such variability and uncertainty in the reconstructed serum lipid AUC estimates for this cohort, depending on elimination model, parameter set, and regression model, have not been described previously and are critical components in evaluating the dose-response data from the occupationally exposed populations.     

A Numerical Solution to the Nonhomogeneous Two-Stage MVK Model of Cancer

In this article, we describe a straightforward method for solving the probability of at least one malignant cell by time t, and the associated hazard function, in the general (i.e., nonhomogeneous) two-stage Moolgavkar-Venzon-Knudson (MVK) model of cancer. The method consists of solving four coupled ordinary differential equations derived from the Kolmogorov backward equations for this process. The relationship of this method to previously proposed solutions is discussed.     

中国蒙古文学史料学的起始与发展

蒙古文学研究的基础和前提是蒙古文学史料。随着国内外蒙古文学研究的不断拓展和深入,蒙古文学史料搜集整理已逐步发展成为蒙古文学史料学。蒙古文学史料学包括蒙古文学的田野调查、史料整理、考订、选录、笺释、校注、校勘、辑评等诸多研究内涵。中国蒙古文学研究取得巨大成就,得益于蒙古文学史料学的长足发展。我们应当总结以往蒙古文学史料学研究的经验,使蒙古文学史料学更加系统化、科学化和理论化。     

Joint impact of multiple observations on a subset of variables in multiple linear regression

In multiple linear regression analysis, each observation affects the fitted regression equation differently and has varying influences on the regression coefficients of the different variables. Chatterjee & Hadi (1988) have proposed some measures such as DSSE_ij (Impact on Residual Sum of Squares of simultaneously omitting the ith observation and the jth variable), F_j (Partial F-test for the jth variable) and F_j(i) (Partial F-test for the jth variable omitting the ith observation) to show the joint impact and the interrelationship that exists among a variable and an observation. In this paper we have proposed more extended form of those measures DSSE_IJ, F_J and F_J(I) to deal with the interrelationships that exist among the multiple observations and a subset of variables by monitoring the effects of the simultaneous omission of multiple variables and multiple observations.     

The impact of social networks on the occupational status of migrants

This paper postulates that there is a continuous exchange of information and knowledge between those who share the common bond of having migrated to the US. The individual components of this information exchange constitute social networks. The 2 hypotheses tested are 1) immediate social networks and people known in the US facilitate the flow of information both to new migrants and between established migrants, thus promoting upward social mobility; and 2) access to broader network ties, organization membership, extra-ethnic friendships, and familiarity with established institutions smooths the transition process, resulting in increased social position. The data used comes from a study conducted in 1982-1983 in 4 Mexican sending communities (2 rural, 2 urban), for a total of 440 migrants. Results show that migrants in every socioeconomic bracket reported access to some or all social network characteristics. There was contact with either a family member or acquaintances from the migrants' town of origin. Over 50% of migrants reported knowing many fellow townspeople. Twice as many migrants belong to a sports club as to a social or religious organization. Very few rural migrants report knowing no townspeople, while 32% of urban migrants claim no knowledge of fellow migrants from their town of origin. Urban origin migrants report more contacts with those of other ethnicity than rural migrants. Those employed in agriculture are least acquainted with social information and contacts, while those in skilled and service sectors are well acquainted with them. The results of fact and analysis show that 1) access to personal US networks results in an average 4.4 point advantage in occupational prestige scores over no access, and 2) utilizing institutional US networks combined with any cumulative US experience gives a migrant a 5 point advantage over a fellow migrant with identical experience level but no institutional network contacts. This is also true for institutional Mexican networks. Thus success or failure in migrating is partly due to migrants' societal infrastructure and the fact that available information and social networks are accessed and utilized differently by different migrants.