On large-sample estimation and testing via quadratic inference functions for correlated data

Hansen (1982) proposed a class of "generalized method of moments" (GMMs) for estimating a vector of regression parameters from a set of score functions. Hansen established that, under certain regularity conditions, the estimator based on the GMMs is consistent, asymptotically normal and asymptotically efficient. In the generalized estimating equation framework, extending the principle of the GMMs to implicitly estimate the underlying correlation structure leads to a "quadratic inference function" (QIF) for the analysis of correlated data. The main objectives of this research are to (1) formulate an appropriate estimated covariance matrix for the set of extended score functions defining the inference functions; (2) develop a unified large-sample theoretical framework for the QIF; (3) derive a generalization of the QIF test statistic for a general linear hypothesis problem involving correlated data while establishing the asymptotic distribution of the test statistic under the null and local alternative hypotheses; (4) propose an iteratively reweighted generalized least squares algorithm for inference in the QIF framework; and (5) investigate the effect of basis matrices, defining the set of extended score functions, on the size and power of the QIF test through Monte Carlo simulated experiments.Comment: 32 pages, 2 figure

Coupling iterated Kolmogorov diffusions

The Kolmogorov (1934) diffusion is the two-dimensional diffusion generated by real Brownian motion B and its time integral integral B d t. In this paper we construct successful co-adapted couplings for iterated Kolmogorov diffusions defined by adding iterated time integrals integral integral B d s d t,... as further components to the original Kolmogorov diffusion. A Laplace-transform argument shows it is not possible successfully to couple all iterated time integrals at once; however we give an explicit construction of a successful co-adapted coupling method for (B, integral B d t, integral integral B d s d t); and a more implicit construction of a successful co-adapted coupling method which works for finite sets of iterated time integrals

Lipopolysaccharide-specific acyloxyacyl hydrolase

" An acyloxyacyl hydrolase from the human promyelocyte cell line HL-60 has been found to specifically hydrolyze fatty acids from their ester linkages to hydroxy groups of 3-hydroxyfatty acids, the latter being being bound in turn to lipopolysaccharide glycosaminyl residues. The hydrolyzed fatty acids may include dodecanoic acid, tetradecanoic acid and hexadecanoic acid. This enzyme showed a molecular weight by gel exclusion chromatography between about 50,000 Daltons and about 70,000 Daltons, and a molecular weight by polyacrylamide gel electrophoresis with sodium dodecylsulphate, using reduced molecular weight standards, of approximately 54,000 to 60,000 Daltons. Altered bacterial lipopolysaccharide substantially without fatty acids bound in ester linkage to hydroxy groups of 3-hydroxyfatty acids covalently linked to a glucosaminyl moiety of lipopolysaccharide lipid A are produced. Since the structure of the lipid A moiety is highly conserved, acyloxyacyl hydrolase may act on lipopolysaccharide of many different pathogenic bacteria (for example Salmonella, Escherichia, Hemophilus, and Neisseria). Such altered bacterial lipopolysaccharide, having toxicity reduced more than immunostimulatory activity, may be therapeutically useful: (1) as vaccines to prevent Gram-negative bacterial diseases by inducing antibodies to lipopolysaccharide O-polysaccharide or R-core antigens, (2) as antidotes to treat or prevent Gram-negative bacterial sepsis (""septic shock""), or (3) as adjuvants to enhance formation of antibodies to other antigens. the acyloxyacyl hydrolase itself may be prophylactically or therapeutically useful to detoxify endogenous lipopolysaccharide in patients with Gram-negative bacterial diseases. The enzyme may also be used to remove toxic lipopolysaccharide from therapeutic injectants. "Board of Regents, University of Texas Syste