A Conversation with Robert V. Hogg

Robert Vincent Hogg was born on November 8, 1924 in Hannibal, Missouri. He earned a Ph.D. in statistics at the University of Iowa in 1950, where his advisor was Allen Craig. Following graduation, he joined the mathematics faculty at the University of Iowa. He was the founding Chair when the Department of Statistics was created at Iowa in 1965 and he served in that capacity for 19 years. At Iowa he also served as Chair of the Quality Management and Productivity Program and the Hanson Chair of Manufacturing Productivity. He became Professor Emeritus in 2001 after 51 years on the Iowa faculty. He is a Fellow of the Institute of Mathematical Statistics and the American Statistical Association plus an Elected Member of the International Statistical Institute. He was President of the American Statistical Association (1988) and chaired two of its winter conferences (1992, 1994). He received the ASA's Founder's Award (1991) and the Gottfried Noether Award (2001) for contributions to nonparametric statistics. His publications through 1996 are described in Communications in Statistics--Theory and Methods (1996), 2467--2481. This interview was conducted on April 14, 2004 at the Department of Statistics, University of Florida, Gainesville, Florida, and revised in the summer of 2006.Comment: Published at http://dx.doi.org/10.1214/088342306000000637 in the Statistical Science (http://www.imstat.org/sts/) by the Institute of Mathematical Statistics (http://www.imstat.org

Distribution-free partial discrimination procedures

AbstractThis paper reviews discrimination procedures which provide distribution-free control over the individual misclassification probabilities. Particular emphasis is placed on the two-population rank method developed by Broffitt, Randles and Hogg, which utilizes the general formulation of Quesenberry and Gessaman. It is shown that the rank method extends from two to three or more populations in a natural and flexible fashion. A Monte Carlo study compares two suggested extensions with others proposed by Broffitt

Label- and amplification-free electrochemical detection of bacterial ribosomal RNA

Current approaches to molecular diagnostics rely heavily on PCR amplification and optical detection methods which have restrictions when applied to point of care (POC) applications. Herein we describe the development of a label-free and amplification-free method of pathogen detection applied to Escherichia coli which overcomes the bottleneck of complex sample preparation and has the potential to be implemented as a rapid, cost effective test suitable for point of care use. Ribosomal RNA is naturally amplified in bacterial cells, which makes it a promising target for sensitive detection without the necessity for prior in vitro amplification. Using fluorescent microarray methods with rRNA targets from a range of pathogens, an optimal probe was selected from a pool of probe candidates identified in silico. The specificity of probes was investigated on DNA microarray using fluorescently labeled 16S rRNA target. The probe yielding highest specificity performance was evaluated in terms of sensitivity and a LOD of 20 pM was achieved on fluorescent glass microarray. This probe was transferred to an EIS end point format and specificity which correlated to microarray data was demonstrated. Excellent sensitivity was facilitated by the use of uncharged PNA probes and large 16S rRNA target and investigations resulted in an LOD of 50 pM. An alternative kinetic EIS assay format was demonstrated with which rRNA could be detected in a species specific manner within 10-40 min at room temperature without wash steps

A method for resolving ties in asymptotic relative efficiency

This article presents a method for determining which of two tests may offer an advantage in power when their asymptotic relative efficiencies (ARE) are the same. The method maintains some of the desirable properties of ARE, such as ease of calculation and singular result based upon asymptotic properties of the tests. However, using higher-order Taylor expansions of the test statistics' means, the procedure offers additional insight into the finite sample size behavior of the tests. Two examples demonstrate the method.Asymptotic relative efficiency ARE Power analysis Asymptotic deficiency Nonparametric statistics

On zeroes in sign and signed rank tests

When zeroes (or ties within pairs) occur in data being analyzed with a sign test or a signed rank test, nonparametric methods textbooks and software consistently recommend that the zeroes be deleted and the data analyzed as though zeroes did not exist. This advice is not consistent with the objectives of the majority of applications. In most settings a better approach would be to view the tests as testing hypotheses about a population median. There are relatively simple p-values available that are consistent with this viewpoint of the tests. These methods produce tests with good properties for testing a different (often more appropriate) set of hypotheses than those addressed by tests that delete the zeroes

Multivariate nonparametric tests of independence

New test statistics are proposed for testing whether two random vectors are independent. Gieser and Randles, as well as Taskinen, Kankainen, and Oja have introduced and discussed multivariate extensions of the quadrant test of Blomqvist. This article serves as a sequel to this work and presents new multivariate extensions of Kendall's tau and Spearman's rho statistics. Two different approaches are discussed. First, interdirection proportions are used to estimate the cosines of angles between centered observation vectors and between differences of observation vectors. Second, covariances between affine-equivariant multivariate signs and ranks are used. The test statistics arising from these two approaches appear to be asymptotically equivalent if each vector is elliptically symmetric. The spatial sign versions are easy to compute for data in common dimensions, and they provide practical, robust alternatives to normal-theory methods. Asymptotic theory is developed to approximate the finite-sample null distributions as well, as to calculate limiting Pitman efficiencies. Small-sample null permutation distributions are also described. A simple simulation study is used to compare the proposed tests with the classical Wilks test. Finally, the theory is illustrated by an example.peerReviewe