University of North Texas

About: University of North Texas is a education organization based out in Denton, Texas, United States. It is known for research contribution in the topics: Population & Poison control. The organization has 11866 authors who have published 26984 publications receiving 705376 citations. The organization is also known as: Fight, North Texas & UNT.

Measurement of C-reactive protein for the targeting of statin therapy in the primary prevention of acute coronary events.

Abstract: Background Elevated levels of C-reactive protein, even in the absence of hyperlipidemia, are associated with an increased risk of coronary events. Statin therapy reduces the level of C-reactive protein independently of its effect on lipid levels. We hypothesized that statins might prevent coronary events in persons with elevated C-reactive protein levels who did not have overt hyperlipidemia. Methods The level of C-reactive protein was measured at base line and after one year in 5742 participants in a five-year randomized trial of lovastatin for the primary prevention of acute coronary events. Results The rates of coronary events increased significantly with increases in the base-line levels of C-reactive protein. Lovastatin therapy reduced the C-reactive protein level by 14.8 percent (P<0.001), an effect not explained by lovastatin-induced changes in the lipid profile. As expected, lovastatin was effective in preventing coronary events in participants whose base-line ratio of total cholesterol to high-de...

Three Likelihood-Based Methods For Mean and Covariance Structure Analysis With Nonnormal Missing Data

Abstract: Survey and longitudinal studies in the social and behavioral sciences generally contain missing data. Mean and covariance structure models play an important role in analyzing such data. Two promising methods for dealing with missing data are a direct maximum-likelihood and a two-stage approach based on the unstructured mean and covariance estimates obtained by the EM-algorithm. Typical assumptions under these two methods are ignorable nonresponse and normality of data. However, data sets in social and behavioral sciences are seldom normal, and experience with these procedures indicates that normal theory based methods for nonnormal data very often lead to incorrect model evaluations. By dropping the normal distribution assumption, we develop more accurate procedures for model inference. Based on the theory of generalized estimating equations, a way to obtain consistent standard errors of the two-stage estimates is given. The asymptotic efficiencies of different estimators are compared under various assump...

Service firms' international entry-mode choice: A modified transaction-cost analysis approach

Abstract: Some peculiar characteristics of service firms, such as low capital intensity and the inseparability of production and consumption, have necessitated the modification of the traditional transaction...