Our colloquia give you the opportunity to learn about research from around campus and across the nation. It's a great way to expand your understanding of statistics and gain exposure to new ways to apply the subject. All colloquia will be held at 2:50 p.m. in LeConte College, Room 210 unless otherwise noted. Refreshments will be served afterward in LeConte 213.
Eric Laber, North Carolina State University
Ding-Geng (Din) Chen, University of North Carolina
Speaker: Lifeng Ling, Florida State University
Affiliation: Texas A&M University, Department of Statistics
Title: Assessing Publication Bias in Meta-Analysis
Abstract: Publication bias is a serious problem in systematic reviews and meta-analyses, which can jeopardize the validity and generalization of conclusions. Current approaches to dealing with publication bias can be distinguished into two classes: selection models and funnel-plot-based methods. Although various statistical methods are available to assess publication bias, their performance has not been systematically evaluated by comprehensive real applications. We compare several commonly-used publication bias tests and evaluate their agreements based on a large collection of meta-analyses from the Cochrane Library. The agreements among most tests are found to be low or moderate. In addition, so far it is popular to test for publication bias, while measures for quantifying publication bias are seldom studied in the literature. Such measures can be used as a characteristic of a meta-analysis, and they permit comparisons of publication biases between different meta-analyses. Egger’s regression intercept is a candidate measure, but it lacks an intuitive interpretation. We introduce a new measure, the skewness of the standardized deviates, to quantify publication bias. This measure describes the asymmetry of the collected studies’ distribution. Also, a new test for publication bias is derived based on the skewness. Large sample properties of the new measure are studied, and its performance is illustrated using simulations and case studies.
Gabriel Huerta, University of New Mexico
Luo Xiao, North Carolina State University
Christine Franklin, University of Georgia
Ling Ma, Clemson University
Palmetto Lecture Series
The Palmetto Lecturer Series is an annual research series begun by former department chair Don Edwards. Each spring, a renowned invited researcher visits the statistics department for a week. During the week, the visitor gives two research presentations (one technical and one more popular/accessible). The list of past Palmetto Lecturers is a glittering one:
- March 26, 2013 Palmetto Lecture on Comparative Inference. Francisco J. Samaniego, University of California, Davis
- March 29, 2013 Palmetto Lecture on Network Reliability. Francisco J. Samaniego, University of California, Davis
- March 25, 2014 Palmetto Lecture on Bayesian Subgroup Reporting. Peter Müller , UT Austin
- March 28, 2014 Palmetto Lecture on Modeling Tumor Heterogeneity. Peter Müller , UT Austin
- March 24, 2016 Palmetto Lecture on Optimal Treatment Regimes. Anastasios (Butch) Tsiatis and Xiaofei Bai, Department of Statistics North Carolina State University
- March 25, 2016 Palmetto Lecture on The SYNERGY Trial. Anastasios (Butch) Tsiatis and Xiaofei Bai, Department of Statistics North Carolina State University
- March 22, 2017 Palmetto Lecture on Data-based Dietary Pattern Scores. Raymond J. Carroll, Texas A&M University
- March 24, 2017 Palmetto Lecture on Estimation using External Data. Raymond J. Carroll, Texas A&M University
In addition to the departmental colloquium series, the statistics department holds regular informal research seminars, often given by faculty and graduate students. Please contact Professor Lianming Wang (firstname.lastname@example.org) if you would like to present a seminar.