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Results for “Regression Analysis”

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At least 163 records · Page 9Linked to original sources

PubMed1994

Immunohistochemical reactivity in mesothelioma and adenocarcinoma: a stepwise logistic regression analysis.

Histological sections from 103 malignant mesotheliomas and 43 adenocarcinoma metastases in pleural biopsies were investigated for reactivity against a panel of 11 different antibodies. The size of the material allowed the evaluation by stepwise logistic regression analysis, which selected five parameters of major importance: vimentin reactivity in epithelial cells, reactivity to low-molecular-weight keratins in fibrous cells, strong membrane accentuation of EMA reactivity, and lack of reactivity to LeuM1 and BerEp4. Three of these criteria were sufficient to identify a mesothelioma with high specificity and with a sensitivity of approximately 70%. Whilst the monoclonal anti-CEA tested was the most valuable single parameter, it did not add any diagnostic information to the combination of criteria selected by the stepwise logistic regression analysis. However, this antibody can be used to exclude most of the adenocarcinomas from further analysis with the more extensive panel.

Adenocarcinoma↗

PubMed1987

Estimation of the operative risk of mitral valve replacement by multivariate logistic regression analysis.

The knowledge of factors determining the risk of postoperative myocardial failure (MF) should allow a more rational approach to the timing and the management of mitral valve replacement (MVR). Using multivariate logistic regression analysis the influence of 41 preoperative and perioperative variables on MF was assessed in a training group of 353 consecutive patients undergoing isolated primary MVR between 6/76 and 12/82. Early MF mortality was 4.2%. Strongest independent preoperative predictors of MF were advanced NYHA functional class (p less than 0.001), hepatomegaly (p = 0.001), and reduced body weight (p = 0.01). Amongst preoperative and perioperative variables independent determinants of MF were NYHA functional class (p less than 0.001), hepatomegaly (p = 0.002), hypotension during extracorporeal circulation (ECC) (p = 0.005), body weight (p = 0.007), ECC duration (p = 0.008), female sex (p = 0.061) and the absence of cardioplegia (p = 0.065). From the combination of these determinants estimates of the probability of MF were calculated and adjoined to low or high risk by means of an optimum cutoff point. The sensitivity of this test performed before and after operation was 0.80 and 0.93, the specificity 0.92 and 0.94, respectively. The reliability of this prognostic test was prospectively evaluated on data of 107 consecutive MVR patients between 1/83 and 12/84. The observed diagnostic characteristics of the test group were comparable to those predicted from the training group. Multivariate logistic regression analysis selects independent determinants, estimates the risk of MF or other modes of postoperative events and identifies patients with low or high risk with a definable validity as an objective aid for medical decision-making.

Bioprosthesis↗

PubMedDate not supplied

A multivariate regression analysis of adolescent multiple drug use in two western Canadian provinces.

This article reports on the results of a multiple regression analysis of an adolescent multiple drug use index on 17 predictor variables from the PRIDE CANADA Drug survey with 18,685 Grades 9 through 12 students in two Western Canadian provinces in 1995-96. The predictor variables represent eight familial, five school and peer, and four individual level attributes and behaviours. The regression analysis is used to estimate the combined effects along with the relative importance of the predictor variables on the students' self-reported use of 11 drugs combined into a multiple drug use index. Separate analyses are conducted for the male and female students. The results indicate that two of the most important predictor variables are the frequency with which both the female and male students report getting into trouble at school and the frequency of the students' participation in worship. The relative importance of these two variables and other variables in relation to the students' multiple use of drugs differ to some extent for the two genders.

Adolescent↗

PubMedDate not supplied

[Regression analysis of an instrumental conditioned tentacular reflex in the edible snail].

Regression analysis revealed the opportunity of approximation with exponential mathematical model of the learning curves of conditioned tentacle reflex. Retention of the reflex persisted for more than three weeks. There were some quantitative differences between conditioning of the right and the left tentacle. There was formation of the reflex in every session during spring period, but there was no retention between sessions. The conditioned tentacle reflex may be employed in neuropharmacological studies.

Animals↗

PubMed1983

The estimation of the time of death by non-protein nitrogen (NPN) in cadaveric materials. Report 3: multiple regression analysis of NPN values in human cadaveric materials.

The non-protein nitrogen (NPN) values in brain, lung, liver, and kidney in 79 autopsy cases were determined according to the Micro-Kjeldahl Nessler method. Multiple regression analysis of the data was performed with every possible combination of the time of death and the NPN values in the tissues. The brain NPN showed the best correlation with the postmortem time (r = 0.673), whereas the other correlations were less satisfactory (lung r = 0.422, liver r = 0.397, and kidney r = 0.379, respectively). However, multiple combinations of each tissue NPN value proved to give better correlation coefficients and smaller errors of the estimated time of death. The practical significance of the tissue NPN as a postmortem biochemical indicator of the time of death and the multiple regression analysis of such indicators were extensively discussed in this report.

Adolescent↗

PubMed2005

[An applied study on Fourier transform near-infrared whole spectroscopy regression analysis].

In the present paper, 66 wheat samples were used as experimental materials, 33 of them were used for building the quantitative analysis model of protein content, and the rest composed the prediction set. Using Moore-Penrose matrix, we estimated directly the regression coefficients of the regression analysis model with Fourier transform near-infrared (FTNIR) whole spectroscopy. The samples of prediction set were analyzed, and the correlation coefficient is 0.979 9 between the prediction values of the near-infrared model and the standard chemical ones by Kjeldahl's method, and the average relative error is 1.76%. Using Moore-Penrose matrix, we can not only get the near-infrared spectroscopy analysis model's regression coefficients, but also know their contribution at every wavelength point. Consequently we can understand and explain the physical and chemical significance of the FTNIR whole spectroscopy regression model.

Plant Proteins↗

PubMed1996

Multiple regression analysis of parameters of lipid and glycide metabolism in obese and lean genetically hypertensive Koletsky rats under long lasting terguride treatment.

Experiments were carried out in the genetically hypertensive obese rats of Koletsky type (SHR/N-cp) and in their lean siblings. Regression analysis was performed when plasma triglycerides was used as a dependent variable and plasma insulin, insulin binding to erythrocytes, basal plasma glucose tolerance data were used as independent variables. Coefficient determination (R2) as well as the tests of hypotheses of regression coefficients being zero were used to indicate which independent variables contributed the least in the explanation of dependent variable. This way we reduced the list of variables to give a simpler regression equation. In the control animals insulinemia was found to be dominant independent variable in all groups except SHR/N-cp obese females where the dominant independent variable was represented by the basal plasma glycaemia. Under the terguride treatment only in SHR/N-cp female rats the dominant independent variable remained the same as in controls. In the other groups the dominant independent variable was different in relation to the control animals. Long lasting terguride treatment normalized hypertriglyceridemia only in SHR/N-cp obese females. Thus the data obtained by multiple regression analysis of parameters of lipide and glycide metabolism show the close relationship to alleviating effect of terguride in hypertriglyceridemia.

Animals↗

PubMed1988

Use of regression analysis and the complement-dependent cytotoxicity typing assay for predicting lymphoid chimerism.

The complement-dependent cytotoxicity typing assay was studied for its accuracy in determining the presence of donor lymphocytes within standard chimeric donor/host cell combinations. Regression analysis of the data was utilized to evaluate the chimera assay. Excellent coefficients of determination (r2 greater than 0.90) were obtained for all standard curves, and a significant (P less than 0.001) linear relationship was established between percent cytotoxicity (dependent variable) and level of donor target cell chimerism (independent variable) for each regression equation. A highly significant (P less than 0.001) linear function was also established between percent cytotoxicity and concentration of donor target bone marrow cells. Regression coefficients (slopes) approached, but did not show complete unity (range; b = 0.86-0.95). Therefore, levels of cytotoxicity were not directly equivalent to levels of donor cell chimerism. A more accurate assessment of donor lymphoid chimerism would be provided by regression analysis of standard donor/host cell independent variables and inverse prediction. Significant estimates of peripheral donor lymphoid chimerism in putative mixed chimeric recipients were successfully made by this technique.

Animals↗

PubMed2006

Neck-focused panic attacks among Cambodian refugees; a logistic and linear regression analysis.

Consecutive Cambodian refugees attending a psychiatric clinic were assessed for the presence and severity of current--i.e., at least one episode in the last month--neck-focused panic. Among the whole sample (N=130), in a logistic regression analysis, the Anxiety Sensitivity Index (ASI; odds ratio=3.70) and the Clinician-Administered PTSD Scale (CAPS; odds ratio=2.61) significantly predicted the presence of current neck panic (NP). Among the neck panic patients (N=60), in the linear regression analysis, NP severity was significantly predicted by NP-associated flashbacks (beta=.42), NP-associated catastrophic cognitions (beta=.22), and CAPS score (beta=.28). Further analysis revealed the effect of the CAPS score to be significantly mediated (Sobel test [Baron, R. M., & Kenny, D. A. (1986). The moderator-mediator variable distinction in social psychological research: conceptual, strategic, and statistical considerations. Journal of Personality and Social Psychology, 51, 1173-1182]) by both NP-associated flashbacks and catastrophic cognitions. In the care of traumatized Cambodian refugees, NP severity, as well as NP-associated flashbacks and catastrophic cognitions, should be specifically assessed and treated.

Adult↗

PubMed2000

Prognostic models based on literature and individual patient data in logistic regression analysis.

Prognostic models can be developed with multiple regression analysis of a data set containing individual patient data. Often this data set is relatively small, while previously published studies present results for larger numbers of patients. We describe a method to combine univariable regression results from the medical literature with univariable and multivariable results from the data set containing individual patient data. This 'adaptation method' exploits the generally strong correlation between univariable and multivariable regression coefficients. The method is illustrated with several logistic regression models to predict 30-day mortality in patients with acute myocardial infarction. The regression coefficients showed considerably less variability when estimated with the adaptation method, compared to standard maximum likelihood estimates. Also, model performance, as distinguished in calibration and discrimination, improved clearly when compared to models including shrunk or penalized estimates. We conclude that prognostic models may benefit substantially from explicit incorporation of literature data.

Age Factors↗

PubMed2005

Recurrence of symptomatic atrial fibrillation after successful catheter ablation of atrioventricular accessory pathways: a multivariate regression analysis.

The primary aim of this study is to investigate the factors related to the recurrence of atrial fibrillation (AF) after a successful ablation of atrioventricular accessory pathway. Thirty-seven patients with spontaneous AF (study group) were selected from 401 consecutive patients who underwent radiofrequency catheter ablation of atrioventricular accessory pathway. A multivariate regression analysis was used in order to evaluate the relationships between AF recurrence and patients' age, sex, atrial size, left ventricular function, location of accessory pathways, heart rate during atrioventricular re-entrant tachycardia and atrial vulnerability (induction of sustained AF) after a successful ablation. Atrioventricular accessory pathway was abolished in 36 of the study group patients and 351 of the control group patients. During the follow-up of 36 +/- 11 months, four patients (11.1%) from the study group experienced sustained AF. Multivariate regression analysis showed that, in patients with pre-ablation AF, older age and post-ablation atrial vulnerability were the only independent predictive factors for AF recurrence. We concluded that radiofrequency catheter ablation of atrioventricular accessory pathway greatly reduces the risk of AF in patients who had a history of symptomatic AF. Older patients and patients with inducible AF after accessory pathway ablation are at an increased risk of AF recurrence. These patients should be closely monitored after successful ablation of atrioventricular accessory pathways.

Adult↗

PubMed2004

Regression analysis of doubly censored failure time data using the additive hazards model.

Doubly censored failure time data arise when the survival time of interest is the elapsed time between two related events and observations on occurrences of both events could be censored. Regression analysis of doubly censored data has recently attracted considerable attention and for this a few methods have been proposed (Kim et al., 1993, Biometrics 49, 13-22; Sun et al., 1999, Biometrics 55, 909-914; Pan, 2001, Biometrics 57, 1245-1250). However, all of the methods are based on the proportional hazards model and it is well known that the proportional hazards model may not fit failure time data well sometimes. This article investigates regression analysis of such data using the additive hazards model and an estimating equation approach is proposed for inference about regression parameters of interest. The proposed method can be easily implemented and the properties of the proposed estimates of regression parameters are established. The method is applied to a set of doubly censored data from an AIDS cohort study.

Acquired Immunodeficiency Syndrome↗

PubMed1992

Use of a spreadsheet program for Deming's linear regression analysis.

A spreadsheet program for Deming's linear regression analysis suitable for use with popular software packages such as Lotus 1-2-3 or Quattro is described. The program is controlled by an autoexecuting simple menu of operations allowing use by those with only limited experience of spreadsheet operation. Regression coefficients, identification of suspect outlying data values and confidence limits and graphical displays of fitted regression lines are provided.

Confidence Intervals↗

PubMed1994

[Epidemiologic features and the stepwise regression analysis of fatal motor vehicle accidents in Guangzhou].

This paper describes the epidemiologic features of 1,532 fatal motor vehicle crashes, and analyses of some crash-related factors by means of stepwise regression analysis as well. The crashes between motor vehicle and bicycle accounted for 39.49 percent. The 36.84 percent of drivers responsible for accidents were at the age of 20-24. The analysis of accident victim characteristics indicated that all age groups were at risk. Most victims were the people younger than 25 years old as well as aged 50 and over. About one-third of the victims were peasants. The analysis of stepwise regression suggested that the crashes were positively related to the quantity of automobile and the ratio between male and female.

Accidents, Traffic↗

PubMed1995

Estimating the diagnostic yields resulting from renography and deconvolution parameters: a logistic regression analysis.

METHODS: Seventy patients with established diagnoses of normal, parenchymally insufficient or acutely obstructed kidneys were subjected to gamma camera renography. Deconvolution was then performed using three main techniques subdivided into six variants. Parameters from time-activity curves as well as retention curves were calculated. Logistic regression analysis was performed to assess the ability of renography and deconvolution methods to differentiate between kidney groups. RESULTS: Discrimination between the groups was achieved by standard renography using six of 17 tested renogram parameters. Based on a set of six curve parameters, the correct classification rates ranged 86%-100%. Five of the six variants of the deconvolution technique used produced similar results. None, however, produced results which were as robust as those from renography. The sixth deconvolution method was consistently worse than the others. CONCLUSION: Standard renography was consistently better than any of the deconvolution techniques used in the separation of the kidney groups. Conceptually, the results of a logistic regression analysis of renogram parameters may raise possibilities in the field of computer-aided diagnosis.

Adolescent↗

PubMed2005

Application of artificial neural network to fMRI regression analysis.

We used an artificial neural network (ANN) to detect correlations between event sequences and fMRI (functional magnetic resonance imaging) signals. The layered feed-forward neural network, given a series of events as inputs and the fMRI signal as a supervised signal, performed a non-linear regression analysis. This type of ANN is capable of approximating any continuous function, and thus this analysis method can detect any fMRI signals that correlated with corresponding events. Because of the flexible nature of ANNs, fitting to autocorrelation noise is a problem in fMRI analyses. We avoided this problem by using cross-validation and an early stopping procedure. The results showed that the ANN could detect various responses with different time courses. The simulation analysis also indicated an additional advantage of ANN over non-parametric methods in detecting parametrically modulated responses, i.e., it can detect various types of parametric modulations without a priori assumptions. The ANN regression analysis is therefore beneficial for exploratory fMRI analyses in detecting continuous changes in responses modulated by changes in input values.

Adult↗

PubMed1987

Hyperbolic regression analysis for kinetics, electrophoresis, ELISA, RIA, Bradford, Lowry, and other applications.

Hyperbolic regression analysis is an effective method for fitting experimental data points obtained from a variety of experiments in molecular biology, including enzyme kinetics, agarose gel electrophoresis of DNA fragments, SDS-polyacrylamide gel electrophoresis of proteins, enzyme-linked immunosorbent assays (ELISA), radioimmunoassays (RIA), Bradford protein quantitation assays, Lowry protein assays, and other applications. Hyperbolic regression yields excellent fitted curves without the biases that are introduced by carrying out linear regression on double reciprocal coordinates, and it produces one simple equation, encompassing all the data points, that can be used easily in a pocket calculator to estimate the values of unknown samples from the known standards.

Algorithms↗

PubMedDate not supplied

Association of balance measures and perception of fall risk on gait speed: a multiple regression analysis.

Gait speed, commonly modified to adapt to the balance and stability challenges of aging, is related to measures of balance and mobility. This study investigated associations between age, Berg Balance Scale, Activities-Specific Balance Confidence (ABC) Scale, One Question Fear of Falling (1QFOF), and gait speed in adults using regression analysis. Results suggested an interaction between 1QFOF and ABC scores. An expanded five-variable model explained 49% of gait speed variance. Age, ABC, and 1QFOF-ABC interactions were significantly associated with gait speed. Regression analysis is useful in investigating associations between performance variables and function. Continued research needs to identify optimal variable combinations and improve prediction of function.

Accidental Falls↗