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PubMedDate not supplied

Linear regression analysis and its application to multivariate chromatographic calibration for the quantitative analysis of two-component mixtures.

Multivariate chromatographic calibration technique was developed for the quantitative analysis of binary mixtures enalapril maleate (EA) and hydrochlorothiazide (HCT) in tablets in the presence of losartan potassium (LST). The mathematical algorithm of multivariate chromatographic calibration technique is based on the use of the linear regression equations constructed using relationship between concentration and peak area at the five-wavelength set. The algorithm of this mathematical calibration model having a simple mathematical content was briefly described. This approach is a powerful mathematical tool for an optimum chromatographic multivariate calibration and elimination of fluctuations coming from instrumental and experimental conditions. This multivariate chromatographic calibration contains reduction of multivariate linear regression functions to univariate data set. The validation of model was carried out by analyzing various synthetic binary mixtures and using the standard addition technique. Developed calibration technique was applied to the analysis of the real pharmaceutical tablets containing EA and HCT. The obtained results were compared with those obtained by classical HPLC method. It was observed that the proposed multivariate chromatographic calibration gives better results than classical HPLC.

Calibration↗

PubMed2004

Navy Asbestos Medical Surveillance Program (1984-1990): linear regression analysis for effect of asbestos exposure on pulmonary function testing.

This study examined records from the Navy Asbestos Medical Surveillance Program for 1984 through 1990 for Caucasian men (N = 129,598) using a population-based, cross-sectional, linear regression model. Continuous dependent variables were forced expiratory volume in 1 s and forced vital capacity (FVC), and continuous independent variables were age, height, weight, and tobacco use. A mid-period estimate of asbestos exposure was used because those values were reported as categorical variables. With asbestos exposure, forced expiratory volume in 1 s changed -3.2 cm3/year (t = -8.6, p = 0.000), and forced vital capacity changed -5.1 cm3/year (t = -11.8, p = 0.00). Those with more than 5 years of asbestos exposure demonstrated impairment over those with less exposure, and those with more than 15 years of exposure demonstrated even more impairment. These findings support the association of pulmonary function impairment with asbestos exposure for workers studied during this period.

Adult↗

PubMed1996

Malignant melanoma risk factors by anatomic site: a case-control study and polychotomous logistic regression analysis.

This population-based case-control study systematically examined reported malignant melanoma risk factors by anatomic site. Study subjects consisted of 548 invasive melanoma cases diagnosed in Connecticut during 1987-1989 and 494 randomly selected controls. Multivariate polychotomous logistic regression was used to determine whether risk factors differed across anatomic sites. Risk factors examined included demographic and pigmentary characteristics, sun exposure-related factors, anatomic site-specific sunburn, recreational water activity clothing habits and number of nevi. A pattern of site-specificity was observed for sunburn. A history of sunburn at an anatomic site was specifically related to the development of malignant melanoma at that site more so than at other sites. This site-specificity was consistent with a direct role for intense, intermittent sun exposure in the development of melanoma. Age and gender were the only risk factors that differed significantly in effect across anatomic sites. The age difference was explained by differences in histologic subtype across sites. The gender difference could not be explained by sex differences in anatomic site-specific sunburns or in recreational water activity clothing habits. Alternative explanations include sex differences in behavioral patterns of sun exposure that we did not measure and as yet unelucidated differences in susceptibility to melanoma according to sex and anatomic site.

Adult↗

PubMed1989

Bayesian regression analysis of non-steady-state phenytoin concentrations: evaluation of predictive performance.

Michaelis-Menten saturable pharmacokinetics confound the determination of appropriate phenytoin maintenance doses. This study retrospectively evaluated the performance of an IBM-PC/XT computer program applying Bayesian regression to the "explicit solution to the Michaelis-Menten equation." Zero to five non-steady-state phenytoin serum concentrations were used to predict either non-steady-state concentrations at least 10 days in the future (n = 49) or steady-state concentrations (n = 20). Non-steady-state concentration prediction precision (% mean absolute error) using 0-5 non-steady-state feedbacks was 137%, 62%, 39%, 31%, 25%, and 15%, respectively, and steady-state concentration prediction precision was 446%, 47%, 50%, 44%, 21%, and 13%, respectively. Elimination of subjects receiving concurrent drugs known to induce phenytoin metabolism significantly improved predictions based on population priors; however, performance improvements were not apparent after two serum level feedbacks. The program provided clinically acceptable predictions with four or more feedbacks. Refinement of population parameters and optimal sampling times should further improve performance.

Aged↗

PubMedDate not supplied

Weighted likelihood, pseudo-likelihood and maximum likelihood methods for logistic regression analysis of two-stage data.

General approaches to the fitting of binary response models to data collected in two-stage and other stratified sampling designs include weighted likelihood, pseudo-likelihood and full maximum likelihood. In previous work the authors developed the large sample theory and methodology for fitting of logistic regression models to two-stage case-control data using full maximum likelihood. The present paper describes computational algorithms that permit efficient estimation of regression coefficients using weighted, pseudo- and full maximum likelihood. It also presents results of a simulation study involving continuous covariables where maximum likelihood clearly outperformed the other two methods and discusses the analysis of data from three bona fide case-control studies that illustrate some important relationships among the three methods. A concluding section discusses the application of two-stage methods to case-control studies with validation subsampling for control of measurement error.

Adult↗

PubMed2003

A multiple logistic regression analysis of in-hospital factors related to survival at six months in patients resuscitated from out-of-hospital ventricular fibrillation.

INTRODUCTION: The impact of the immediate in-hospital post-resuscitation care after out-hospital cardiac arrest is not well known. Based on treatment variables and laboratory findings a multiple logistic regression model was created for the prediction of survival at 6 months from the event. MATERIALS AND METHODS: A retrospective study of the hospital charts of patients successfully resuscitated and treated in one of three community hospitals from 1998 to 2000. In addition to several pre-hospital variables, the mean 72 h values of clinical features such as blood pressure, blood glucose concentration and initiated treatment used, were included in a forward multiple logistic regression model predicting survival at 6 months from the event. RESULTS: The charts of 98 out of a total of 102 patients were sufficiently complete and included in the analysis. Variables independently associated with survival were age, delay before a return of spontaneous circulation, mean blood glucose and serum potassium, and the use of beta-blocking agents during post-resuscitation care. When those patients who were assigned a 'do not attempt to resuscitate' (DNAR) order during the first 72 h of treatment were excluded from the analysis blood glucose, blood potassium and the use beta-blocking agents remained independently associated with survival. CONCLUSION: This study suggests that in-hospital factors are associated with survival from out-of-hospital cardiac arrest. The mean blood glucose and serum potassium during the first 72 h of treatment and the use of beta-blocking agents were significantly and independently associated with survival.

Adrenergic beta-Antagonists↗

PubMed2000

Discriminant and multiple regression analysis of anemia and opportunistic infection in Fell pony foals.

A condition resembling acquired immunodeficiency with anemia has been described in British Fell pony foals. The pathogenesis is unknown. The present study involved 322 foals of which 164 were of Fell breed and 12 were affected. Discriminant and multiple regression analyses were used to test the results of all clinical pathology parameters from these foals for statistical association with (1) breed origin and (2) presence of disease. Only hematocrit associated significantly with presence of disease. However, significant associations were found with Fell breed origin, including serum albumin concentration and lymphocyte count. The unexpected discovery of sporadic lymphocytosis in the breed indicates the value of this kind of analysis and may be evidence that Fell foal immunodeficiency is associated with retroviral infection.

Journal Article↗

PubMed2005

Generalized linear regression analysis of association of universal helmet laws with motorcyclist fatality rates.

This study evaluates the association of universal helmet laws with U.S. motorcyclist fatality rates from 1993 through 2002 using climate measures as statistical controls for motorcycling activity via quasi-maximum likelihood generalized linear regression analyses. Results revealed that motorcyclist fatalities and injuries are strongly associated with normalized heating degree days and precipitation inches, and that universal helmet laws are associated with lower motorcyclist fatality rates when these climate measures, and their interaction, are statistically controlled. This study shows that climate measures have considerable promise as indirect measures (proxies) of motorcycling activity in generalized linear regression studies.

Accidents, Traffic↗

PubMed2002

Real-time modelling of influenza outbreaks--a linear regression analysis.

Seasonal outbreaks of influenza exert a considerable burden on health services, and are notorious for their variability from year to year. Making use of historical data from the Scottish sentinelle surveillance since 1972, a potential candidate model has been derived based on simple linear regression. It was applied with a measure of success in the 1999-2000 winter season.

Disease Outbreaks↗

PubMed2004

[The morbidity of chronic diabetic complication with logistic regression analysis of related potential risk factors].

OBJECTIVE: To investigate the morbidity and potential risk factors of chronic diabetic complication in Zhejiang province. METHODS: In the paper the morbidity of diabetic chronic complication was illustrated, using descriptive statistics. The potential risk factors of diabetic chronic complication were studied with logistic regression modeling, using data from a large retrospective study involving 1083 patients from two hospitals in Zhejiang province. RESULTS: Principal chronic diabetic complications were found to be cardiovascular diseases, ophthalmic diseases, nephropathy, esthetic diseases, plant nerve diseases, cerebral blood vessel diseases, limbsblood vessel diseases and athletic nerve diseases. The principal potential risk factors would include the courses of diabetes and hypertension, age, age being diagnosed, blood pressure, baseline blood glucose, two hour blood glucose after dietary, HBAIC, nitroglycerine, cholesterol, high density lipoprotein cholesterol and low density lipoprotein cholesterol. CONCLUSION: The analytic method used in the paper was fit for the study of morbidity and potential risk factors of other chronic diseases complication and the discriminant function could be built for clinical diagnosis.

China↗

PubMed2003

Comparative investigation of superoxide trapping by cyclic nitrone spin traps: the use of singular value decomposition and multiple linear regression analysis.

The kinetics of the reaction between superoxide and the spin trapping agents 5,5-dimethyl-1-pyrroline N-oxide (DMPO), 5-(diethoxyphosphoryl)-5-methyl-1-pyrroline N-oxide (DEPMPO), and 5-tert-butoxycarbonyl-5-methyl-1-pyrroline N-oxide (BMPO) were re-examined in the superoxide-generating xanthine/xanthine oxidase system, by competition with spontaneous dismutation. The approach used singular value decomposition (SVD), multiple linear regression, and spectral simulation. The experiments were carried out using a two-syringe mixing arrangement with fast scan acquisition of 100 consecutive EPR spectra. Using SVD analysis, the extraction of both temporal and spectral information could be obtained from in a single run. The superoxide spin adduct was the exclusive EPR active species in the case of DEPMPO and BMPO, and the major component when DMPO was used. In the latter case a very low concentration of hydroxyl adduct was also observed, which did not change during the decay of the DMPO-superoxide adduct. This indicates that the hydroxyl radical adduct is not formed from the spontaneous decay of the superoxide radical adduct, as has been previously suggested [correction]. It was established that in short-term studies (up to 100 s) DMPO was the superior spin trapping agent, but for reaction times longer than 100 s the other two spin traps were more advantageous. The second order rate constants for the spin trapping reaction were found to be DMPO (2.4 M(-1)s(-1)), DEPMPO (0.53 M(-1)s(-1)), and BMPO (0.24 M(-1)s(-1)) determined through competition with spontaneous dismutation of superoxide, at pH 7.4 and 20 degrees C.

Cyclic N-Oxides↗

PubMed1991

[Logistic regression analysis of risk factors influencing the occurrence of category III pneumoconiosis in the coal mine].

Using 1:4 matched method, we have selected 40 cases of category III pneumoconiosis and 160 controls in a coal mine, and analyzed the factors which influenced the occurrence of category III pneumoconiosis by Multiple Logistic Regression Model. The results were as follows: Tuberculous infection and the type of radiographic appearance manifested mainly as small round opacities were positively correlated with the attack of category III pneumoconiosis. The time of starting exposure to dust, the years and the kinds of work were not led into regression model as significant factors.

Case-Control Studies↗

PubMed1982

Regression analysis of the central visual field in chronic glaucoma cases. A follow-up study using automatic perimetry.

90 glaucoma cases (160 eyes) with field defects in at least one eye have been subjected to automatic perimetry on at least 5 occasions. The condition of the field defect is represented by the regression coefficient. The frequency distribution of the coefficients in groups based on references to age, sex, intraocular pressure, exfoliations, haemorrhages and therapy illustrates the possible importance or insignificance of these factors to the decay. The need for several consecutive examinations to establish with some significance a progression of field defects is demonstrated.

Age Factors↗

PubMed2004

Navy Asbestos Medical Surveillance Program (1991-1999): linear regression analysis for the effect of asbestos exposure on pulmonary function testing.

The effect of asbestos exposure on pulmonary function was studied using data from the Navy Asbestos Medical Surveillance Program. Records were selected for Caucasian men from 1991 to 1999 (N = 89,318) and were analyzed using a cross-sectional, linear regression model. Dependent variables were forced expiratory volume in 1 s (FEV1) and forced vital capacity (FVC), with independent continuous variables of age, height, weight, smoking, and asbestos history. Overall, the continuous variable for asbestos exposure demonstrated significant protection of +1.1 cm3/year (t = 3.278, p = 0.001) for FEV1 and +1.6 cm3/year (t = 4.225, p = 0.000) for FVC. There was significant interaction between asbestos exposure and smoking history (FEV1, -0.09 cm3/year2, t = -6.467, p = 0.000; FVC, -0.097 cm3/year2, t = -5.663, p = 0.000). This study suggests that workers within the program demonstrated minimal additional pulmonary function changes during the period, particularly if they do not smoke tobacco. The study also supports continuing smoking cessation efforts for all asbestos-exposed workers.

Adult↗

PubMed2006

Prediction of intra-twin birth weight discordance by binary logistic regression analysis.

AIMS: Identification of women at high risk of intra-twin birth weight discordance is helpful in obstetric care of these pregnancies. The aim of this study is to establish an intra-twin birth weight discordance prediction model. METHODS: We created an intra-twin birth weight discordance prediction model by logistic regression, based on the 1995-1997 register twin birth data of the USA. The twin sets were randomly divided into two groups: group 1 to establish the prediction model and group 2 to validate the prediction model. Intra-twin birth weight discordance was defined as birth weight discordance > 25%. The prediction model was validated by receiver operating characteristic curve. RESULTS: A birth weight discordance prediction model including maternal age (beta = 0.069), parity (beta = 0.250), fetal gender concordance (beta = 0.041), maternal hypertension (beta = 0.368), eclampsia (beta = 0.316), other medical complication (beta = 0.165), and smoking (beta = 0.164) was established, yielded a 0.558 area under the receiver operating characteristic curve. The sensitivity, specificity, and positive predictive values were 38.1, 69.7, and 10.8%, respectively, at the cut-off value of 0.09 in group 2. CONCLUSION: A birth weight discordance prediction model that includes seven variables available during pregnancy has been established with acceptable diagnostic performance.

Area Under Curve↗

PubMed2003

Comparing hierarchical modeling with traditional logistic regression analysis among patients hospitalized with acute myocardial infarction: should we be analyzing cardiovascular outcomes data differently?

BACKGROUND: Data in health research are frequently structured hierarchically. For example, data may consist of patients treated by physicians who in turn practice in hospitals. Traditional statistical techniques ignore the possible correlation of outcomes within a given practice or hospital. Furthermore, imputing characteristics measured at higher levels of the hierarchy to the patient-level artificially inflates the amount of available information on the effect of higher-level characteristics on outcomes. METHODS: Conventional logistic regression models and multilevel logistic regression models were fit to a cross-sectional cohort of patients hospitalized with a diagnosis of acute myocardial infarction. The statistical significance of the effect of patient, physician, and hospital characteristics on patient outcomes was compared between the 2 modeling strategies. RESULTS: The 2 analytic strategies agreed well on the effect of patient characteristics on outcomes. According to the traditional analysis, teaching status was statistically significantly associated with 5 of the 9 outcomes, whereas the multilevel models did not find a statistically significant association between teaching status and any patient outcomes. Similarly, the traditional and multilevel models disagreed on the statistical significance of the effect of being treated at a revascularization hospital and 3 patient outcomes. CONCLUSIONS: In comparing the resultant models, we see that false inferences can be drawn by ignoring the structure of the data. Conventional logistic regression tended to increase the statistical significance for the effects of variables measured at the hospital-level compared to the level of significance indicated by the multilevel model.

Adult↗

PubMed2001

Internal validation of predictive models: efficiency of some procedures for logistic regression analysis.

The performance of a predictive model is overestimated when simply determined on the sample of subjects that was used to construct the model. Several internal validation methods are available that aim to provide a more accurate estimate of model performance in new subjects. We evaluated several variants of split-sample, cross-validation and bootstrapping methods with a logistic regression model that included eight predictors for 30-day mortality after an acute myocardial infarction. Random samples with a size between n = 572 and n = 9165 were drawn from a large data set (GUSTO-I; n = 40,830; 2851 deaths) to reflect modeling in data sets with between 5 and 80 events per variable. Independent performance was determined on the remaining subjects. Performance measures included discriminative ability, calibration and overall accuracy. We found that split-sample analyses gave overly pessimistic estimates of performance, with large variability. Cross-validation on 10% of the sample had low bias and low variability, but was not suitable for all performance measures. Internal validity could best be estimated with bootstrapping, which provided stable estimates with low bias. We conclude that split-sample validation is inefficient, and recommend bootstrapping for estimation of internal validity of a predictive logistic regression model.

Aged↗

PubMed1994

Cox regression analysis of multivariate failure time data: the marginal approach.

Multivariate failure time data are commonly encountered in scientific investigations because each study subject may experience multiple events or because there exists clustering of subjects such that failure times within the same cluster are correlated. In this paper, I present a general methodology for analysing such data, which is analogous to that of Liang and Zeger for longitudinal data analysis. This approach formulates the marginal distributions of multivariate failure times with the familiar Cox proportional hazards models while leaving the nature of dependence among related failure times completely unspecified. The baseline hazard functions for the marginal models may be identical or different. Simple estimating equations for the regression parameters are developed which yield consistent and asymptotically normal estimators, and robust variance-covariance estimators are constructed to account for the intra-class correlation. Simulation results demonstrate that the large-sample approximations are adequate for practical use and that ignoring the intra-class correlation could yield rather misleading variance estimators. The proposed methodology has been fully implemented in a simple computer program which also incorporates several alternative approaches. Detailed illustrations with data from four clinical or epidemiologic studies are provided.

Adolescent↗