Search PubMed⌕ Search

SEARCH · Search PubMed

Results for “Statistical Regression”

Search indexed PubMed citations on genomics, clinical trials, systematic reviews and public health. Explore titles, authors and supplied subject terms, then open the PubMed record.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 541 records · Page 30Linked to original sources
PubMed1992

Placebo effects in standard human neuropharmacological studies: effects of physiological variations of blood glucose and ammonia concentration on the electrophysiology of the visual system.

The effects on retinal and cortical visual evoked phenomena of the stimulus intensity/spatial frequency and of the spontaneous, physiological blood glucose/ammonia fluctuations were investigated comparatively in a pilot study on young male volunteers. Flash ERG and flash OPs to 5 different stimulus intensities and pattern VECP to 3 spatial frequencies were recorded at 2-hour intervals during a standard acute pharmaco-EEG experimental session (8 h) with administration of placebo; glucose and ammonia blood concentration levels were assessed concomitantly. The effects of the stimulus intensity/spatial frequency were statistically defined for each amplitude/latency measure by nonlinear regression analysis and were removed by computing the residuals from the regression function, which were then tested separately versus the glucose/ammonia concentration by linear regression. Glucose/ammonia statistically significant effects on the visual system were detected at concentration levels within the range of normality and were representative of a nonnegligeable portion of the data overall variance. These effects were selective on retinal/cortical evoked phenomena and it is conceivable that physiological or pathological metabolic changes might account for a still underestimated source of individual variability in human neuropharmacological studies otherwise adequately controlled.

Adult↗
PubMed2005

Statistics review 14: Logistic regression.

This review introduces logistic regression, which is a method for modelling the dependence of a binary response variable on one or more explanatory variables. Continuous and categorical explanatory variables are considered.

Humans↗
PubMed1985

[Long-term prognosis of drug and surgery treated patients with acquired aortic valve diseases: survival statistics and multivariate Cox regression analysis].

Data of 417 patients with advanced chronic aortic valve disease were retrospectively analyzed using a life table and Cox regression analysis. Aortic valve replacement was recommended to all patients based on clinical and hemodynamic findings. While most patients underwent prosthetic aortic valve replacement (n = 349), a minority of patients was treated medically (n = 68). Prognosis was better (p less than 0.01 in the Cox model) in surgically treated as compared to medically treated patients with aortic stenosis (4-year survival rate 82 versus 44%). In patients with aortic insufficiency no significant difference of long-term prognosis was found between surgically and medically treated patients.

Anti-Bacterial Agents↗
PubMed2005

Phase III trial of ursodeoxycholic acid to prevent colorectal adenoma recurrence.

BACKGROUND: Ursodeoxycholic acid (UDCA) treatment is associated with a reduced incidence of colonic neoplasia in preclinical models and in patients with conditions associated with an increased risk for colon cancer. We conducted a phase III, double-blind placebo-controlled trial of UDCA to evaluate its ability to prevent colorectal adenoma recurrence. METHODS: We randomly assigned 1285 individuals who had undergone removal of a colorectal adenoma within the past 6 months to daily treatment with UDCA (8-10 mg/kg of body weight; 661 participants) or with placebo (624 participants) for 3 years or until follow-up colonoscopy. Recurrence rates (number of recurrent adenomas per unit time) were compared by use of a Huber-White variance estimator. Proportions of participants with one or more recurrent adenomas were compared with a Pearson chi-square statistic; adjusted odds ratios (ORs) were obtained by logistic regression. All statistical tests were two-sided. RESULTS: We observed a non-statistically significant 12% reduction in the adenoma recurrence rate associated with UDCA treatment, compared with placebo treatment. However, UDCA treatment was associated with a statistically significant reduction (P = .03) in the recurrence of adenomas with high-grade dysplasia (adjusted OR = 0.61, 95% confidence interval = 0.39 to 0.96). We observed no statistically significant differences between UDCA and placebo groups in recurrence with regard to adenoma size, villous histology, or location. CONCLUSIONS: UDCA treatment was associated with a non-statistically significant reduction in total colorectal adenoma recurrence but with a statistically significant 39% reduction in recurrence of adenomas with high-grade dysplasia. Because severely dysplastic lesions have a high risk of progression to invasive colorectal carcinoma, this finding indicates that future chemoprevention trials of UDCA in individuals with such lesions should be considered.

Adenoma↗
PubMedDate not supplied

Effects of model sensitivity and nonlinearity on nonlinear regression of ground water flow.

Nonlinear regression is increasingly applied to the calibration of hydrologic models through the use of perturbation methods to compute the Jacobian or sensitivity matrix required by the Gauss-Newton optimization method. Sensitivities obtained by perturbation methods can be less accurate than those obtained by direct differentiation, however, and concern has arisen that the optimal parameter values and the associated parameter covariance matrix computed by perturbation could also be less accurate. Sensitivities computed by both perturbation and direct differentiation were applied in nonlinear regression calibration of seven ground water flow models. The two methods gave virtually identical optimum parameter values and covariances for the three models that were relatively linear and two of the models that were relatively nonlinear, but gave widely differing results for two other nonlinear models. The perturbation method performed better than direct differentiation in some regressions with the nonlinear models, apparently because approximate sensitivities computed for an interval yielded better search directions than did more accurately computed sensitivities for a point. The method selected to avoid overshooting minima on the error surface when updating parameter values with the Gauss-Newton procedure appears for nonlinear models to be more important than the method of sensitivity calculation in controlling regression convergence.

Models, Statistical↗
PubMed1993

A twelve-year profile of students' SAT scores, GPAs, and MCAT scores from a small university's premedical program.

PURPOSE: To determine whether significant correlations existed among quantitative and qualitative predictors of students' academic success and quantitative outcomes of such success over a 12-year period in a small university's premedical program. METHOD: A database was assembled from information on the 199 graduates who earned BS degrees in biology from Barry University's School of Natural and Health Sciences from 1980 through 1991. The quantitative variables were year of BS degree, total score on the Scholastic Aptitude Test (SAT), various measures of undergraduate grade-point averages (GPAs), and total score on the Medical College Admission Test (MCAT); and the qualitative variables were minority (54% of the students) or majority status and transfer (about one-third of the students) or nontransfer status. The statistical methods were multiple analysis of variance and stepwise multiple regression. RESULTS: Statistically significant positive correlations were found among SAT total scores, final GPAs, biology GPAs versus nonbiology GPAs, and MCAT total scores. These correlations held for transfer versus nontransfer students and for minority versus majority students. Over the 12-year period there were significant fluctuations in mean MCAT scores. CONCLUSION: The students' SAT scores and GPAs proved to be statistically reliable predictors of MCAT scores, but the minority or majority status and the transfer or nontransfer status of the students were statistically insignificant.

Education, Premedical↗
PubMed2005

Omnibus hypothesis testing in dominance-based ordinal multiple regression.

Often quantitative data in the social sciences have only ordinal justification. Problems of interpretation can arise when least squares multiple regression (LSMR) is used with ordinal data. Two ordinal alternatives are discussed, dominance-based ordinal multiple regression (DOMR) and proportional odds multiple regression. The Q2 statistic is introduced for testing the omnibus null hypothesis in DOMR. A simulation study is discussed that examines the actual Type I error rate and power of Q2 in comparison to the LSMR omnibus F test under normality and non-normality. Results suggest that Q2 has favorable sampling properties as long as the sample size-to-predictors ratio is not too small, and Q2 can be a good alternative to the omnibus F test when the response variable is non-normal.

Data Collection↗
PubMed2005

137Cs in freshwater fish in Finland since 1986--a statistical analysis with multivariate linear regression models.

The accident at the Chernobyl nuclear power plant in 1986 significantly elevated the 137Cs levels of fish in Finnish lakes. About 6200 fish samples from 390 lakes comprising 20 species have been analysed for 137Cs since 1986. The sizes of the lakes varied from a few hectares to about 1000 km2. Activity concentrations of 137Cs in fish still varied widely in 2003, from 16 to 6400 Bq/kg fresh weight. This paper presents the results of statistical analyses with multivariate linear regression models carried out on the empirical data collected since 1986. The statistical analysis resulted in separate models for two time periods describing temporal changes of 137Cs in fish. The explanatory variables were fish species with various feeding habits, the size class of the lake, municipal division, drainage area, time since the deposition and deposition level of the municipality. The calculated values for 137Cs in fish did not differ statistically significantly from the observed values in the validation data. The explanatory variables explained 58% (the first time period) and 72% (the second time period) of the total variability of 137Cs in fish.

Animal Feed↗
PubMed1997

Bootstrapping regression parameters in multivariate survival analysis.

Bootstrap methods are proposed for estimating sampling distributions and associated statistics for regression parameters in multivariate survival data. We use an Independence Working Model (IWM) approach, fitting margins independently, to obtain consistent estimates of the parameters in the marginal models. Resampling procedures, however, are applied to an appropriate joint distribution to estimate covariance matrices, make bias corrections, and construct confidence intervals. The proposed methods allow for fixed or random explanatory variables, the latter case using extensions of existing resampling schemes (Loughin, 1995), and they permit the possibility of random censoring. An application is shown for the viral positivity time data previously analyzed by Wei, Lin, and Weissfeld (1989). A simulation study of small-sample properties shows that the proposed bootstrap procedures provide substantial improvements in variance estimation over the robust variance estimator commonly used with the IWM.

Acquired Immunodeficiency Syndrome↗
PubMed2000

Using conditional logistic regression to fit proportional odds models to interval censored data.

An easily implemented approach to fitting the proportional odds regression model to interval-censored data is presented. The approach is based on using conditional logistic regression routines in standard statistical packages. Using conditional logistic regression allows the practitioner to sidestep complications that attend estimation of the baseline odds ratio function. The approach is applicable both for interval-censored data in settings in which examinations continue regardless of whether the event of interest has occurred and for current status data. The methodology is illustrated through an application to data from an AIDS study of the effect of treatment with ZDV+ddC versus ZDV alone on 50% drop in CD4 cell count from baseline level. Simulations are presented to assess the accuracy of the procedure.

Acquired Immunodeficiency Syndrome↗
PubMed2001

Moderated multiple regression for interactions involving categorical variables: a statistical control for heterogeneous variance across two groups.

Moderated multiple regression (MMR) arguably is the most popular statistical technique for investigating regression slope differences (interactions) across groups (e.g., aptitude-treatment interactions in training and differential test score-job performance prediction in selection testing). However, heterogeneous error variances can greatly bias the typical MMR analysis, and the conditions that cause heterogeneity are not uncommon. Statistical corrections that have been developed require special calculations and are not conducive to follow-up analyses that describe an interaction effect in depth. A weighted least squares (WLS) approach is recommended for 2-group studies. For 2-group studies, WLS is statistically accurate, is readily executed through popular software packages (e.g., SAS Institute, 1999; SPSS, 1999), and allows follow-up tests.

Humans↗