PubMed Health⌕ Search

SEARCH · PubMed Health

Results for “Regression Analysis”

Explore indexed PubMed citations for clinical trials, systematic reviews and public health research. Read source abstracts and follow each citation to its original PubMed record.

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

At least 91 records · Page 5Linked to original sources
PubMed1997

Regression analysis of simulated radio-ligand equilibrium experiments using seven different mathematical models.

The objective of this study was to investigate the conditions for regression analysis of data from equilibrium experiments. One important issue was to recognize that Kd and the binding site concentration (A) are not of equal nature, although both are parameters in the regression analysis. Whereas Kd approximates to a true constant, A is subject to experimental variation due to pipetting errors and in solid-phase experiments also to uneven coating properties. While recognizing that the ideal assumptions for ordinary regression analysis are poorly satisfied, different regression models were evaluated by extensive simulations. It was first established by a 'worst case' investigation that a limited error (8%) in the dependent variable is not critical for the results obtained at curve-fitting to Langmuir's equation. Seven different equations were compared for the calculation of data representing a solid-phase equilibrium experiment with statistical but no systematic errors. All the equations are rearrangements of the law of mass action. In this setting the Scatchrd plot gave the best result, but also the double reciprocal and the Woolf plots worked well in weighted analysis. Langmuir's equation gave the best result of the 4 nonlinear regression models tested. The influence of one type of systematic error was also investigated. This assumed that 10% of the label was positioned on particles other than the functional ligand molecules. This systematic error was amplified, which resulted in a substantial bias. The calculated Kd-values varied slightly with the regression method used and were almost 24% too high in the best methods.

Bias↗
PubMed2005

Estimation of early postmortem intervals by a multiple regression analysis using rectal temperature and non-temperature based postmortem changes.

Five general methods based on rectal temperature and a multiple regression analysis using rectal temperature and non-temperature based postmortem changes were applied to 212 postmortem cases of within 24h postmortem (PM) intervals. Non-temperature based postmortem changes of rigidity, hypostasis and corneal turbidity were numerically categorized and used with rectal temperatures as four statistical variables in the multiple regression analysis. The correlation coefficient values between true and calculated postmortem intervals were 0.78-0.82 in the five general methods based on rectal temperature. The multiple regression analysis produced a multiple correlation coefficient value of 0.89 and according to the error ranges of the PM intervals, 72% of the cases were estimated within the error of +/-1.0 h and 92% within +/-5.0 h. Although assessments of non-temperature based PM changes are mostly subjective and have a wide variation, the present study demonstrated a usefulness of non-temperature based PM changes in the estimation of PM intervals.

Adolescent↗
PubMed1993

Method for detection of intracellular pH threshold; comparison between subjective observation and regression analysis.

The aim of this study is to examine the objectivity and reproducibility of intracellular pH threshold (pHT) detected by eye (E), and by regression analysis on linear (L), semilog (SL) and log-log (LL) models. Threshold for inorganic phosphate-to-phosphocreatine ratio (PT) was also examined by three regression analysis. Fifteen males volunteered as subjects. They performed wrist flexion in a ramp protocol of 0.14W/min till exhaustion. Throughout the exercise, 31P-MRS was obtained continuously from wrist flexors. Intracellular pH and phosphate compound in the muscle tissue were monitored as minute-by-minute data. In E, three observers determined pHT subjectively as a work rate just before pH decrement. In three regression analysis, pHT was detected as an intersection of a pair of linear regression lines which was selected statistically or subjectively. pHT detected by four methods showed significant reproducibility between each other, although PT did not. These results provide one of the evidences of threshold behavior of change in pH, and a question of existence of PT in contrast to pHT.

Exercise↗
PubMed2006

[Heidelberg Retina Tomograph II topographic parameters, diagnostic capabilities of moorfields regression analysis, and their affecting factors].

PURPOSE: To investigate optic disc topographic parameters at every stage in glaucoma patients and to compare results with data from normal Japanese subjects. We used a Heidelberg Retina Tomograph II (HRT II), to evaluate the sector diagnostic capabilities of Moorfields regression analysis in early glaucoma patients, and to determine whether there is a correlation between the background factors and either the topographic parameters or the diagnostic capabilities. SUBJECTS AND METHODS: We measured topographic parameters using HRT II, and examined static visual fields in 303 normal and 130 glaucoma eyes without high refractive error. RESULTS: Mean disc area was 2.181 +/- 0.384 mm2 in the normal Japanese subjects. At the time visual field loss first appeared, disc damage was already advanced. Moorfields regression analysis of sensitivity and specificity was 81.3% and 90.1%, respectively, for early glaucoma. The best diagnostic precision was found in the temporal/inferior sector. Correlations were noted for normal subject topographic parameters and the disc area, age, sex, and conus, but not for Moorfields regression analysis and the disc area, refractive error, age, and sex, even though diagnostic capabilities declined with the presence of conus. CONCLUSIONS: HRT II is more useful in glaucoma diagnosis than in follow-up. Focus should be on the temporal/inferior sector as well as on the overall Moorfields regression analysis. Also, close attention should be paid to the presence of conus.

Aged↗
PubMed1998

A comparison of linear and orthogonal regression analysis for local INR determination in ECAA coagulometer studies. European Concerted Action on Anticoagulation.

International sensitivity index calibrations based on the W.H.O. recommended method depend on orthogonal regression analysis. As this is not readily available in statistical packages, comparison has been made with simple linear regression analysis in a study of coagulometer effects on the International Normalized Ratio (INR) at 155 European centres. Sets of seven lyophilized normal and 20 lyophilized artificially depleted abnormal plasmas were provided with five coumarin test plasmas and two European Concerted Action on Anticoagulation reference thromboplastins (low International Sensitivity Index (ISI) human and high ISI rabbit). Local ISI based on the artificially depleted lyophilized plasmas using conventional orthogonal regression gave good correction for local coagulometer effects on the human reagent and minimal correction with the rabbit reagent INR. Results were considerably worse after attempts at correction using calibration based on linear regression analysis with both reagents. The results indicate that calibration of coagulometer prothrombin time systems using simple linear regression is not appropriate.

Animals↗
PubMed2000

Assessment of the bioavailability of rare earth elements in soils by chemical fractionation and multiple regression analysis.

The bioavailability of rare earth elements (REEs) in soils was evaluated, based on the combination of chemical fractionation and multiple regression analysis. REEs in soils were partitioned by a sequential extraction procedure into water soluble (F(ws)), exchangeable (F(ec)), bound to carbonates (F(cb)), bound to organic matter (F(om)), bound to Fe-Mn oxides (F(fm)) and residual (F(rd)) fractions. Alfalfa (Medicago Staiva Linn.) had been grown on the soils in a pot-culture experiment under greenhouse conditions for 35 days. The concentrations of REEs in fractions and plant were determined by inductively coupled plasma-mass spectrometry (ICP-MS). Chemical fractionation showed that (F(ws)) fraction of REEs was less than 0.1% and residual (F(rd)) was the dominant form, more than 60% in soils. Bioaccumulation of REEs was observed in Alfalfa. REE availability to the plant was evaluated by multiple regression analysis. F(ws), F(ec), F(cb) and F(om) fractions were significantly correlated with REE uptake by alfalfa. But the exchangeable Pr(F(ec)) was significantly correlated with Pr concentration in alfalfa. F(ec), F(cb) and F(om) greatly contributed to La and Nd bioavailability; F(ec) and F(om) to Ce, Gd and Dy; F(ec) and F(cb) to Yb; and F(ws), F(ec) and F(om) to total REEs. This meant that the bioavailability of different species of REEs varied with individual REE. The results of this study indicated that the sequential extraction procedure, in conjunction with multiple regression analysis, may be useful for the prediction of plant uptake of REEs from soils.

Biological Availability↗
PubMed2002

Improved statistical characterization of prosthetic heart valve hydrodynamics using a performance index and regression analysis.

BACKGROUND AND AIMS OF THE STUDY: The ISO 5840 Standard (Cardiovascular implants - Cardiac valves) currently requires a minimum of three test samples per size for hydrodynamic testing. Typically, the only statistical analysis performed is a descriptive analysis, with the mean (+/- SE) given for each size and cardiac output (CO). The study aim was to develop better statistical methods, incorporating regression analysis of a performance index, equal to the effective orifice area divided by the tissue annulus area. The analysis is performed on the full dataset, with size and CO as independent variables. METHODS: Hydrodynamic data of Ionescu-Shiley pericardial valves from a published study were used to compare the two analysis methods. Three samples each of size 19, 23 and 27 mm valves were tested at COs of 4.2, 5.6, 7.0 and 8.4 l/min. Descriptive statistics were performed for each size and CO. Regression analysis was also performed on the full dataset. Confidence intervals (CI) were calculated for each statistical method and compared. RESULTS: The regression equation that best fitted the data was: Performance Index (PI) = -1.63 + (0.011 x CO) + (0.167 x size) - (0.0036 x size2). All four parameter estimates were significantly different from zero (p <0.02). The SE of the mean was 0.015 for COs of 4.2 or 8.4 l/min, and 0.013 for COs of 5.6 or 7.0 l/min, less than that of nine of 12 of the individual descriptive analysis. CI for the regression analysis were substantially tighter, averaging one-third the width of those of the descriptive statistics. CONCLUSION: The tighter CI resulting from the regression analysis allows a better comparison of the PI to an objective performance criterion. Such methods should be considered for inclusion in the new version of the ISO 5840 standard for prosthetic heart valves.

Aortic Valve↗
PubMed1987

The relationship between antidepressant response and tricyclic antidepressant plasma concentrations. A retrospective analysis of the literature using logistic regression analysis.

The relationship between the antidepressant effect of the tricyclic antidepressants and their plasma concentrations was reviewed. Logistic regression was utilised as an analytical tool to facilitate the evaluation. The currently available literature allowed the construction of 4 tricyclic data sets of sufficient size to warrant statistical analysis. Inspection of the distribution of the data and the logistic regression analyses resulted in several conclusions regarding the existence of 'therapeutic windows' for these drugs. Firstly, no relationship between amitriptyline plasma concentrations and therapeutic response was apparent. Secondly, curvilinear relationships were apparent for 2 of the other tricyclic antidepressants studied. The currently recommended therapeutic range of 60 to 150 micrograms/L for nortriptyline was found to be the range most likely to produce a positive antidepressant effect. Desipramine concentrations between 108 and 158 micrograms/L were most commonly associated with beneficial therapeutic responses. Finally, a linear relationship was noted for imipramine in which an imipramine therapeutic plasma concentration threshold of 244 micrograms/L and above was most commonly associated with a beneficial response to the drug.

Animals↗
PubMed1998

Prognostic factors in restoration of pulmonary flow after submassive pulmonary embolism: a multiple regression analysis.

Defects as evaluated by lung perfusion scans may persist even 6 months after pulmonary embolism (PE), when treatment is withdrawn. The aim of this study was to evaluate the effect of several potential factors on the resolution of lung perfusion defects, both during the first days and at 6 months, when patients were discharged. In a retrospective follow-up cohort study we included 102 patients with PE, diagnosed lung from a ventilation/perfusion (V'/Q') scan, following Prospective Investigation of Pulmonary Embolism Diagnosis (PIOPED) criteria, together with a phlebographic study of lower extremities or angiography. Lung perfusion scan was performed at diagnosis, and in two follow-up evaluations, at 7-10 days and at 6 months. Potential factors studied were: age; sex; presence of underlying cardiac or pulmonary disease; venous insufficiency; alveolar-arterial pressure difference for oxygen; delay in diagnosis; abnormalities in electrocardiogram or chest radiograph; and the size of defects as shown in lung perfusion scans. All factors were studied with regards to the size of the defects at the two follow-up evaluations, through a univariate statistical analysis and two multiple stepwise regression analysis. Multivariate statistical analysis selected four factors: size of defects at diagnosis; prior cardiopulmonary disease; delay in diagnosis; and sex, as synergistic variables to predict defect size at 7-10 days. On the other hand, the defect size at 7-10 days was the only variable selected as a predictor of the size of defects at 6 months. Resolution of pulmonary defects during the first days after diagnosis of pulmonary embolism is influenced by the initial defect size, prior cardiopulmonary diseases and sex. The size of residual defects at 6 months depends mainly on the size of defects at 7-10 days.

Cohort Studies↗
PubMed1988

Multiple regression analysis of twin data: etiology of deviant scores versus individual differences.

The multiple regression analysis of twin data in which a cotwin's score is predicted from a proband's score and the coefficient of relationship (the basic model) provides a statistically powerful test of genetic etiology. When an augmented model that also contains an interaction term is fitted to the same data set, direct estimates of heritability (h2) and the proportion of variance due to shared environmental influences (c2) are obtained. A simple transformation of selected twin data prior to regression analysis facilitates direct estimates of h2g (an index of the extent to which the difference between the mean of probands and that of the unselected population is heritable) and a test of the hypothesis that the etiology of deviant scores differs from that of variation within the normal range.

Data Interpretation, Statistical↗
PubMed1999

EasyBound--a user-friendly approach to nonlinear regression analysis of binding data.

The introduction of non-linear regression analysis of data from pharmacological experiments has provided an enormous advantage in making it possible to analyze raw data without any mathematical transformation. However, the disadvantage has been the lack of computer programs with simple user interfaces and the ability to easily handle large amounts of data. With the aim to develop a light-weight and still powerful program we have written an application called EasyBound which is designed to be used with Microsoft Excel and hence takes advantage of the abilities of the spreadsheet application to handle large amounts of data. Focus has been on creating an easy-to-understand user interface. There are commercial programs available, but they tend to be very complex and difficult to grasp for inexperienced users. EasyBound displays original data, calculated results and graphs on the same sheet/page. The program fully implements the most powerful algorithms for non-linear regression analysis, giving results that are more accurate than using built-in iterative analysis functions of the spreadsheet application without compromising ease of use.

Algorithms↗
PubMedDate not supplied

Topological evidence of differential oncogene activation-tumor suppressor gene inactivation features in 10 human neoplasias, as revealed by sequential regression analysis of world cancer incidence data.

Recent progress in the molecular biology of cancer research indicates that oncogene activation and tumor suppressor gene inactivation are the two key events in the carcinogenesis of humans as well as of animals. The purpose of this investigation was to assess separately the impact of oncogene activation and tumor suppressor gene inactivation on the genesis of a given neoplasia using the log-transformed age-adjusted incidence rates (log AAIRs) data from 47 cancer registration areas world wide. In practice, the sequential regression analysis test was applied to each of 15 (male) or 16 (female) tumor pairs, in which the neoplasia in question (marker tumor) was designated as the common x partner in the calculation of the 1st order regression equation. The correlation coefficient of the sequential regression analysis, r seq, served as an index of fitness to the equilibrium models of both oncogene activation and tumor suppressor gene inactivation, in which the expected values of r seq for sole oncogene activation and sole tumor suppressor gene inactivation were each -1.00 and +1.00. The calculation results with the sequential regression analysis were given as the profile of 15 (male) or 16 (female) r seq data for each marker tumor. The r seq profile of a given neoplasia was also prepared using each the original coordinates (the "Org" coordinates) and 2 variant coordinates (the "Rect" coordinates and the "Para" coordinates). The "Rect" and the "Para" coordinates were so designed as to allow their x-axes to run at a right angle and parallel to the regression line of the tumor pair data block. Results obtained are as follows: a) The "Org" coordinates gave an oncogene activation- type r seq profile for each of all marker tumors tested; b) The "Rect" coordinates gave a tumor suppressor inactivation-type r seq profile for each of all marker tumors tested; c) The r seq profile of the "Para" coordinates was classified as of the intermediate type as regards the direction (+ or -) as well as the amplitude of r seq values; d) Remarkable amplification of oncogene activation was noted in the r seq profile of the dominant gender as compared with the recessive gender in 3 cancers with sex-discriminant cancer risks (cancers of the esophagus, liver and breast). In summary, the use of the "Org"- and the "Rect"-coordinates in the sequential regression analysis was found to be useful for assessing separately the impact of oncogene activation and tumor suppressor gene inactivation on the genesis of a tumor. Amplification of oncogene activation was very often responsible for the emergence of sex difference in cancer risk. The association of the 2 coordinates with the 2 contrasting r seq profiles was explained by the topology of the tumor pair data distribution in the 2 dimensional diagram. Finally, the findings with sex-differential tumors are discussed in the light of the steroid carcinogenesis hypothesis.

Female↗
PubMed2003

Prediction of human pharmacokinetics from animal data and molecular structural parameters using multivariate regression analysis: volume of distribution at steady state.

The aim of this study was to develop a regression equation for predicting volume of distribution at steady state (Vd(ss)) in humans to enable application to various types of drugs using animal experimental data for rats and dogs and some molecular structural parameters. The Vd(ss) data for rats, dogs and humans of 64 drugs were obtained from literature. The compounds have various structures, pharmacological activities and pharmacokinetic characteristics. In addition, the molecular weight, calculated partition coefficient (clogP), and the number of hydrogen bond acceptors were used as possible descriptors related to the Vd(ss) in humans. Multivariate regression analyses, multiple linear regression analysis and the partial least squares (PLS) method were used to predict Vd(ss) in humans. Interaction terms were also introduced into the regression analysis to evaluate the non-linear relationship. For the data set used in the present study, PLS with quadratic term descriptors gave the best predictive performance. The PLS model using Vd(ss) data for only two animal species and using easily calculated structural parameters could generally predict Vd(ss) in humans better than an allometric method. In addition, the PLS model with only animal data gave almost the same predictive performance as the PLS model with quadratic term descriptors. This model may be easier to use and be practical in a realistic situation, and could predict Vd(ss) in humans better than the allometric method.

Animals↗
PubMedDate not supplied

Estimation of melanin and hemoglobin in skin tissue using multiple regression analysis aided by Monte Carlo simulation.

To estimate the concentrations of melanin and blood and the oxygen saturation in human skin tissue, we propose a method using a multiple regression analysis aided by a Monte Carlo simulation for diffuse reflectance spectra from the skin tissue. By using the absorbance spectrum as a response variable and the extinction coefficients of melanin, oxygenated hemoglobin, and deoxygenated hemoglobin as predictor variables, the multiple regression analysis gives regression coefficients. The concentrations of melanin and blood are determined from the regression coefficients using conversion vectors that are estimated numerically in advance, while the oxygen saturation is obtained directly from the regression coefficients. Numerical and experimental investigations were performed for layered skin tissue models and phantoms. Measurements of human skin were also carried out to monitor variations in the melanin and blood contents and oxygenation during cuff occlusion. The results confirmed the usefulness of the proposed method.

Algorithms↗
PubMed1992

Rationale for using multiple regression analysis with complex interferences.

Non-specificities and interferences may become complex when they involve the analyte as well as other interfering substances. These non-specificities and interferences are known as analyte-dependent and multi-interferent interferences. Multiple regression analysis has proven valuable in analysing this type of interference, but the theoretical foundation for using multiple regression analysis to study the basic mechanisms of interference has not been explicitly demonstrated. Graph theory can depict and model the basic mechanisms of interferences and the possible interactions. The relationship between the analyte, the interferents, and the response of the instrument to these entities can be approximated by a polymial of order three, which includes partial derivatives and cross-terms. The partial derivatives relate to the different interactions found with the graph theory model. Further, the partial derivatives can be associated with the coefficients in the multiple regression analysis when the respective values of the three variables (analyte, interferent one, and interferent two) are multiplied by one another. One can decide to retain or discard the coefficient of a variable, based on the statistical significance of the coefficient. The respective interactions in the graphic model can then be assembled and the framework of the interference mechanism established.

Bilirubin↗
PubMed2004

Modeling of complex viscosity changes in the curing of epoxy resins from near-infrared spectroscopy and multivariate regression analysis.

The present study investigates the relationship between the changes in complex viscosity and near-infrared spectra. Principal component regression analysis is applied to a near-infrared data set obtained from the in situ monitoring of the curing of diglycidyl ether of bisphenol A with the diamine 4,4'-diaminodiphenylmethane. The values of complex viscosity obtained by dynamic mechanical analysis during the cure process were used as a reference. The near-infrared spectra recorded throughout the reaction, unlike the univariate data analysis at some wavelengths of the spectra, contain a sufficient amount of information to estimate the complex viscosity. The relationship found was high and the results demonstrate the quality of the fitted model. Also, a simple user-friendly procedure for applying the model, focused on the user, is shown.

Algorithms↗
PubMed2005

Poisson regression analysis of ungrouped data.

BACKGROUND: Poisson regression is routinely used for analysis of epidemiological data from studies of large occupational cohorts. It is typically implemented as a grouped method of data analysis in which all exposure and covariate information is categorised and person-time and events are tabulated. AIMS: To describe an alternative approach to Poisson regression analysis using single units of person-time without grouping. METHODS: Data for simulated and empirical cohorts were analysed by Poisson regression. In analyses of simulated data, effect estimates derived via Poisson regression without grouping were compared to those obtained under proportional hazards regression. Analyses of empirical data for a cohort of 138 900 electrical workers were used to illustrate how the ungrouped approach may be applied in analyses of actual occupational cohorts. RESULTS: Using simulated data, Poisson regression analyses of ungrouped person-time data yield results equivalent to those obtained via proportional hazards regression: the results of both methods gave unbiased estimates of the "true" association specified for the simulation. Analyses of empirical data confirm that grouped and ungrouped analyses provide identical results when the same models are specified. However, bias may arise when exposure-response trends are estimated via Poisson regression analyses in which exposure scores, such as category means or midpoints, are assigned to grouped data. CONCLUSIONS: Poisson regression analysis of ungrouped person-time data is a useful tool that can avoid bias associated with categorising exposure data and assigning exposure scores, and facilitate direct assessment of the consequences of exposure categorisation and score assignment on regression results.

Adolescent↗