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At least 757 records · Page 42Linked to original sources
PubMed1997

Categorical regression analysis of acute exposure to tetrachloroethylene.

Exposure-response analysis of acute noncancer risks should consider both concentration (C) and duration (T) of exposure, as well as severity of response. Stratified categorical regression is a form of meta-analysis that addresses these needs by combining studies and analyzing response data expressed as ordinal severity categories. A generalized linear model for ordinal data was used to estimate the probability of response associated with exposure and severity category. Stratification of the regression model addresses systematic differences among studies by allowing one or more model parameters to vary across strata defined, for example, by species and sex. The ability to treat partial information addresses the difficulties in assigning consistent severity scores. Studies containing information on acute effects of tetrachloroethylene in rats, mice, and humans were analyzed. The mouse data were highly uncertain due to lack of data on effects of low concentrations and were excluded from the analysis. A model with species-specific concentration intercept terms for rat and human central nervous system data improved fit to the data compared with the base model (combined species). More complex models with strata defined by sex and species did not improve the fit. The stratified regression model allows human effect levels to be identified more confidently by basing the intercept on human data and the slope parameters on the combined data (on a C x T plot). This analysis provides an exposure-response function for acute exposures to tetrachloroethylene using categorical regression analysis.

Administration, Inhalation↗
PubMed1994

Multiple regression analysis of cytogenetic human data.

Biomonitoring studies on cytogenetic outcomes in humans should be considered as epidemiological studies, rather than randomized trials. Under this light the emphasis given to the achievement of a significant p-value should be reduced, since this measure suffers from major limitations. The use of a point estimate (and its corresponding confidence interval) to measure the association between exposure and effect offers several advantages, including the adjustment for confounding, and the evaluation of possible interaction between factors. In most instances the use of multivariate statistical methods allows an efficient analysis of these studies, even in presence of a small sample size and several covariates. In this paper we re-analyzed four biomonitoring studies by using multivariate methods to estimate relative risks through statistical modeling. The use of multiple regression techniques allowed the computation of point estimates of association and their confidence intervals for each covariate evaluated by the studies considered; the estimate of the effect of confounding variables such as smoking habits, age and gender; and the presence of interaction between covariates. Measures of association estimated through univariate and multivariate statistical approaches are compared. The advantages of the latter technique are discussed.

Adult↗
PubMed1991

The factors affecting plasma glutathione peroxidase and selenium in rheumatoid arthritis: a multiple linear regression analysis.

The reactive oxygen radicals are trapped by anti-oxidants, such as selenium containing glutathione peroxidase (GSHpx), which also can inhibit the oxygenation of arachidonic acid to pro-inflammatory prostaglandins and leukotrienes. We studied the levels of anti-oxidant glutathione peroxidase and selenium (in plasma) in 48 patients with rheumatoid arthritis (RA). In the multiple regression model, joint score had the highest explanatory value for serum selenium, and sulphasalazine treatment was the most significant variable contributing to GSHpx activity. The plasma GSHpx activity was not increased in RA patients in general, but was high in those taking sulphasalazine as compared with those not doing so (342.4 +/- 48.2 vs. 298.9 +/- 34.7 U/l, 95% confidence interval of difference from 17.9 to 69.1, p less than 0.002). The serum selenium levels correlated with clinical activity of the joint, disease measuring joint score.

Adult↗
PubMed1994

Logistic regression analysis of twin data: estimation of parameters of the multifactorial liability-threshold model.

We extend the DeFries-Fulker regression model for the analysis of quantitative twin data to cover binary traits and genetic dominance. In the proposed logistic regression model, the cotwin's trait status, C, is the response variable, while the proband's trait status, P, is a predictor variable coded as k (affected) and 0 (unaffected). Additive genetic effects are modeled by the predictor variable PR, which equals P for monozygotic (MZ) and P/2 for dizygotic (DZ) twins; and dominant genetic effects, by PD, which equals P for MZ and P/4 for DZ twins. By setting an appropriate scale for P (i.e., the value of k), the regression coefficients of P, PR, and PD are estimates of the proportion of variance in liability due to common family environment, additive genetic effects, and dominant genetic effects, respectively, for a multifactorial liability-threshold model. This model was applied to data on lifetime depression from the Virginia Twin Registry and produced results similar to those from structural equation modeling.

Adult↗
PubMed1986

Logistic regression analysis of incidental-tumor data from animal carcinogenicity experiments.

Survival differences can have a substantial impact on the statistical comparison of tumor development in control and treated animals and thus should be taken into account routinely in the analysis of carcinogenicity data from laboratory experiments. However, the appropriate survival adjustment depends on whether the tumor of interest is fatal or incidental. The usual analysis of incidental tumors, which adjusts for survival by stratifying the animals according to age at death, has various shortcomings. Alternatively, logistic regression methods allow a continuous survival adjustment and furnish a convenient framework for solving many of the problems associated with the age-stratified approach of grouping the data into time intervals. Logistic regression substitutes modeling the prevalence function for the arbitrary choice of time intervals, providing a survival adjustment (when the model holds) even when differential mortality might increase the bias or decrease the sensitivity of interval-based methods. The logistic analysis also can incorporate covariables which, if ignored, might confound the interpretation of the data. Several examples illustrate these potential advantages of basing the analysis of incidental tumors on logistic regression techniques.

Aging↗
PubMed2000

Determinants of outcomes in laparoscopic colorectal surgery: a multiple regression analysis of 416 resections.

BACKGROUND: To date, most large series of laparoscopic colorectal procedures have been descriptive reports that do not account for the potentially complex interaction of outcome predictors. The purpose of this study was to identify the preoperative factors that predict operative time, conversion to open surgery, and intraoperative and postoperative complications in laparoscopic colorectal surgery. METHODS: Multiple regression techniques were used to analyze 416 laparoscopic resections from a prospective database of laparoscopic colorectal procedures performed between April 1991 and April 1998. The preoperative factors considered were patient-specific (age, gender, weight) or disease-specific (diagnosis of cancer, Crohn's disease, diverticulitis, fistula). Surgical experience of < or =50 cases was also considered. Finally, all resections were represented by a combination of the following five procedure components: resections of the (a) hepatic flexure, (b) splenic flexure, (c) sigmoid, and (d) rectum, or (e) a perineal dissection. RESULTS: Patient weight, Crohn's disease, and each of the five individual procedure components incrementally lengthened operative time. Conversion to open surgery was influenced by the patient's weight, malignancy, and early experience of the surgeon. The risk of a postoperative complication was increased by the patient's age, resection of the perineum, and the presence of a fistula. No factors significantly influenced the risk of an intraoperative complication. CONCLUSIONS: Several preoperative factors that significantly affect outcomes in laparoscopic colorectal resections have been identified. Consideration of these factors may help in case selection and estimation of operating time; they should also be valuable when patients are informed of their risk of conversion and complications.

Adolescent↗
PubMed1987

A regression analysis program to fit nonseparable equations.

A program to perform a nonlinear best fit for separable and nonseparable equations is described. This software is written in Turbo-Pascal so that it can be run both on CP/M systems or PC-DOS systems; in the latter, graphics can be performed using the Turbo Graphix Toolbox. From initial estimates the regression coefficients as well as the statistics are calculated. Two examples are shown: one of a separable equation describing receptor binding; the second of a nonseparable equation, describing the displacement of labeled agonist by an inhibitor. The only difference in the fit between a separable and a nonseparable equation is that the latter requires iterations for an estimate of the dependent variable every time that new regression coefficients are calculated.

Microcomputers↗
PubMed1996

A computer program for regression analysis of ordered categorical repeated measurements.

RMORD is an easy-to-use FORTRAN program for the analysis of clustered ordinal data using the method of Stram, Wei, and Ware. This method constitutes an extension of the proportional-odds model to the situation in which groups of responses are correlated. At each measurement occasion, a proportional-odds regression model is fit to the data by maximizing the occasion-specific likelihood function. The joint asymptotic distribution of the occasion-specific regression parameter estimators is obtained along with a consistent estimator of their asymptotic covariance matrix. RMORD may be used when ordinal measurements are obtained at a common set of observation times for multiple subjects or clusters. Both missing data and covariates which vary within clusters can be accommodated. The program can be run on microcomputers, workstations, and mainframe computers. Two examples illustrating the usage and features of RMORD are provided.

Age Distribution↗
PubMed1990

Ranking the risk factors for cesarean: logistic regression analysis of a nationwide study.

The risk factors that influenced the decision to perform cesarean were ranked in a nationwide census of deliveries conducted in Israel. The study encompassed 22,815 women who gave birth between November 1, 1983 and January 31, 1984 in the 30 maternity departments in the country; 2179 deliveries were by emergency cesarean. Multivariate stepwise logistic regression technique indicated that the most important risk factors affecting the decision were the presentation of the fetus and the presence of a uterine scar, followed in descending order by placenta previa or abruptio placentae, maternal disease, primiparity, low birth weight, twins, and advanced maternal age. The mother's ethnic background and type of hospital played an insignificant role in the decision-making process. The specific statistical method applied in this work permits listing the indicators that constitute risk factors for cesarean and provides the net effect of each factor on the decision-making process.

Cesarean Section↗
PubMed1984

The impact of child mortality on spacing by parity: a Cox-regression analysis.

Child mortality may affect spacing through biological and behavioral channels. The death of a child may elicit a desire to have another one soon; further, it may interrupt breastfeeding and shorten the sterile period following childbirth. The hypothesis that the child mortality-spacing linkage varies across parities, being strongest in the middle parities, is examined using microdata from Malaysia and the Cox-regression technique. The empirical results lend support to the hypothesis.

Adult↗