NIST hosts Conference on Designs for Generalized Linear Models. (General Developments).Celebrating the 30th anniversary of the Nelder and Wedderburn paper introducing generalized linear models Not to be confused with general linear model. In statistics, the generalized linear model (GLM) is a useful generalization of ordinary least squares regression. It relates the random distribution of the measured variable of the experiment (the (GLMs), NIST (National Institute of Standards & Technology, Washington, DC, www.nist.gov) The standards-defining agency of the U.S. government, formerly the National Bureau of Standards. It is one of three agencies that fall under the Technology Administration (www.technology. hosted the Conference on Designs for Generalized Linear Models in Gaithersburg in April 2002. The primary goal of the conference was to provide a forum for interaction among researchers working on diverse areas of designs for GLMs. A main focus was on the problem of design dependency on the unknown parameters of the model. Secondary goals of the conference included the sharing of GLM GLM Global Language Monitor GLM Global Marine (stock symbol) GLM Graduated Length Method (ski instruction) GLM Good Looking Mom (used in pediatric practices) GLM God Loves Me design methodology across application areas and the introduction and stimulation of young researchers and graduate students in the GLM design area. The concept of GLMs, as a unified class of regression models for discrete and continuous variables, was first introduced by Nelder and Wedderburn in their seminal 1972 JRSS/A paper. Since that time, GLMs have served as a paradigm for a large class of problems in applied statistics and have been used routinely in dealing with observational studies observational studies, n.pl an investigational method involving description of the associations be-tween interventions and outcomes. Outcomes research and practice audits are examples of this investigational method. . GLMs have proven very effective in several application areas ranging from medicine to economics to quality control to sample surveys. Many statistical developments in terms of modeling and methodology, in the past twenty years TWENTY YEARS. The lapse of twenty years raises a presumption of certain facts, and after such a time, the party against whom the presumption has been raised, will be required to prove a negative to establish his rights. 2. , may be viewed as special cases of GLMs. The conference opened with Nelder's presentation about the introduction and history of GLMs and closed with a panel discussion about the future of GLMs. Other technical sessions covered optimal and two-stage designs, sequential designs, generalized linear mixed models, comparison of designs for logistic models logistic models, n.pl statistical models that describe the relationship between a qualitative dependent variable (that is, one that can take only certain discrete values, such as the presence or absence of a disease) and an independent variable. and industrial split-plot experiments, and designs for variance components estimation. CONTACT: Ivelisse Aviles, (301) 975-2849; ivelisse. aviles@nist.gov. |
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