Translog Cost Function Estimation: Banking Efficiency

This paper examines the selection of data source and econometric technique for studies of banking efficiency using translog cost functions. We examine the use of Seemingly Unrelated Regression estimation for a cost function, as against estimation using Ordinary Least Squares. Choice of cost data to feed to the estimation is also important, and we find that use of wage and interest data may sometimes be superior to cost data inferred from bank accounting information. Lastly, we discuss filtering of data, where some observations may contain erroneous or noisy data

Unbiased estimation in seamless phase II/III trials with unequal treatment effect variances and hypothesis-driven selection rules.

Seamless phase II/III clinical trials offer an efficient way to select an experimental treatment and perform confirmatory analysis within a single trial. However, combining the data from both stages in the final analysis can induce bias into the estimates of treatment effects. Methods for bias adjustment developed thus far have made restrictive assumptions about the design and selection rules followed. In order to address these shortcomings, we apply recent methodological advances to derive the uniformly minimum variance conditionally unbiased estimator for two-stage seamless phase II/III trials. Our framework allows for the precision of the treatment arm estimates to take arbitrary values, can be utilised for all treatments that are taken forward to phase III and is applicable when the decision to select or drop treatment arms is driven by a multiplicity-adjusted hypothesis testing procedure. © 2016 The Authors. Statistics in Medicine Published by John Wiley & Sons Ltd

Correcting for bias in the selection and validation of informative diagnostic tests.

When developing a new diagnostic test for a disease, there are often multiple candidate classifiers to choose from, and it is unclear if any will offer an improvement in performance compared with current technology. A two-stage design can be used to select a promising classifier (if one exists) in stage one for definitive validation in stage two. However, estimating the true properties of the chosen classifier is complicated by the first stage selection rules. In particular, the usual maximum likelihood estimator (MLE) that combines data from both stages will be biased high. Consequently, confidence intervals and p-values flowing from the MLE will also be incorrect. Building on the results of Pepe et al. (SIM 28:762-779), we derive the most efficient conditionally unbiased estimator and exact confidence intervals for a classifier's sensitivity in a two-stage design with arbitrary selection rules; the condition being that the trial proceeds to the validation stage. We apply our estimation strategy to data from a recent family history screening tool validation study by Walter et al. (BJGP 63:393-400) and are able to identify and successfully adjust for bias in the tool's estimated sensitivity to detect those at higher risk of breast cancer

Accounting for selection and correlation in the analysis of two-stage genome-wide association studies.

The problem of selection bias has long been recognized in the analysis of two-stage trials, where promising candidates are selected in stage 1 for confirmatory analysis in stage 2. To efficiently correct for bias, uniformly minimum variance conditionally unbiased estimators (UMVCUEs) have been proposed for a wide variety of trial settings, but where the population parameter estimates are assumed to be independent. We relax this assumption and derive the UMVCUE in the multivariate normal setting with an arbitrary known covariance structure. One area of application is the estimation of odds ratios (ORs) when combining a genome-wide scan with a replication study. Our framework explicitly accounts for correlated single nucleotide polymorphisms, as might occur due to linkage disequilibrium. We illustrate our approach on the measurement of the association between 11 genetic variants and the risk of Crohn's disease, as reported in Parkes and others (2007. Sequence variants in the autophagy gene IRGM and multiple other replicating loci contribute to Crohn's disease susceptibility. Nat. Gen. 39: (7), 830-832.), and show that the estimated ORs can vary substantially if both selection and correlation are taken into account

Does Tolerance Reflect a More Inclusive Self-Construal? A Comparison of Poland, East and West Germany

Past research suggests that Poland and Germany differ in the inclusiveness of their “moral universe”, i.e. the breadth of the community to which people apply moral values and rules of fairness (Schwartz, 2007). It seems likely that this difference is reflected in a more or less inclusive definition of one’s ingroup. The present study investigated (1) whether there are indeed differences in ingroup inclusiveness as manifested in differential construals of the self in East and West Germany and Poland and (2) whether those differences are reflected in differences in tolerance. As expected, participants in West Germany had the most inclusive self-construal, followed by participants from East Germany and then Poland – both in terms of their absolute scores on the most inclusive level (being a member of humanity), and in terms of the relative importance of the different levels. A relationship between a more inclusive self-construal and tolerance was observed in West Germany, but not in East Germany and Poland. The results suggest that more inclusive and abstract levels of the self-construal are more closely linked to other abstract constructs such as values rather than a true reflection of people’s ingroup. In countries with a communist past where universal values or the concern for humanity at large have been used for ideological purposes, these values may have lost their original meaning and psychological significance, and are less linked to intergroup attitudes such as tolerance towards immigrants

Translog Cost Function Estimation: Banking Efficiency

This paper examines the selection of data source and econometric technique for studies of banking efficiency using translog cost functions. We examine the use of Seemingly Unrelated Regression estimation for a cost function, as against estimation using Ordinary Least Squares. Choice of cost data to feed to the estimation is also important, and we find that use of wage and interest data may sometimes be superior to cost data inferred from bank accounting information. Lastly, we discuss filtering of data, where some observations may contain erroneous or noisy data

Hundreds of variants clustered in genomic loci and biological pathways affect human height

Most common human traits and diseases have a polygenic pattern of inheritance: DNA sequence variants at many genetic loci influence the phenotype. Genome-wide association (GWA) studies have identified more than 600 variants associated with human traits, but these typically explain small fractions of phenotypic variation, raising questions about the use of further studies. Here, using 183,727 individuals, we show that hundreds of genetic variants, in at least 180 loci, influence adult height, a highly heritable and classic polygenic trait. The large number of loci reveals patterns with important implications for genetic studies of common human diseases and traits. First, the 180 loci are not random, but instead are enriched for genes that are connected in biological pathways (P = 0.016) and that underlie skeletal growth defects (P < 0.001). Second, the likely causal gene is often located near the most strongly associated variant: in 13 of 21 loci containing a known skeletal growth gene, that gene was closest to the associated variant. Third, at least 19 loci have multiple independently associated variants, suggesting that allelic heterogeneity is a frequent feature of polygenic traits, that comprehensive explorations of already-discovered loci should discover additional variants and that an appreciable fraction of associated loci may have been identified. Fourth, associated variants are enriched for likely functional effects on genes, being over-represented among variants that alter amino-acid structure of proteins and expression levels of nearby genes. Our data explain approximately 10% of the phenotypic variation in height, and we estimate that unidentified common variants of similar effect sizes would increase this figure to approximately 16% of phenotypic variation (approximately 20% of heritable variation). Although additional approaches are needed to dissect the genetic architecture of polygenic human traits fully, our findings indicate that GWA studies can identify large numbers of loci that implicate biologically relevant genes and pathways.

Multigroup Ethnic Identity Measure (MEIM) Expansion: Measuring Racial, Religious, and National Aspects of Sense of Ethnic Identity Within the United Kingdom

These studies examined the degree to which racial, religious, and national aspects of individuals' sense of ethnic identity stand as interrelated, yet distinct, constructs. Results of exploratory factor analyses in Study 1 (n = 272) revealed that a three-factor model specifying racial, religious, and national identities yielded optimal fit to correlational data from an expanded, 36-item version of the Multigroup Ethnic Identity Measure (MEIM; Roberts et al., 1999), although results left room for improvement in model fit. Subsequently, results of confirmatory factor analyses in Study 2 (n = 291) revealed that, after taking covariance among the items into account, a six-factor model specifying exploration and commitment dimensions within each of the racial, religious, and national identity constructs provided optimal fit. Implications for the utility of Goffman's (1963b) interactionist role theory and Erikson's (1968) ego psychology for understanding the full complexity of felt ethnic identity are discussed

New genetic loci link adipose and insulin biology to body fat distribution.

Body fat distribution is a heritable trait and a well-established predictor of adverse metabolic outcomes, independent of overall adiposity. To increase our understanding of the genetic basis of body fat distribution and its molecular links to cardiometabolic traits, here we conduct genome-wide association meta-analyses of traits related to waist and hip circumferences in up to 224,459 individuals. We identify 49 loci (33 new) associated with waist-to-hip ratio adjusted for body mass index (BMI), and an additional 19 loci newly associated with related waist and hip circumference measures (P < 5 × 10(-8)). In total, 20 of the 49 waist-to-hip ratio adjusted for BMI loci show significant sexual dimorphism, 19 of which display a stronger effect in women. The identified loci were enriched for genes expressed in adipose tissue and for putative regulatory elements in adipocytes. Pathway analyses implicated adipogenesis, angiogenesis, transcriptional regulation and insulin resistance as processes affecting fat distribution, providing insight into potential pathophysiological mechanisms