[Aprindine in the treatment of chronic premature ventricular contractions. Evaluations based on the two-way analysis of variance and linear regression analysis].
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Administration, Oral↗
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Results for “Regression Analysis”
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Alternatives to least squares linear regression analysis for computation of standard curves for quantitation by high performance liquid chromatography: applications to clinical pharmacology.
Standard curves and validation points for high-performance liquid chromatography (HPLC) determination of four drugs (carbamazepine and phenytoin at therapeutic drug monitoring concentrations and deuterium labeled carbamazepine and phenytoin at tracer dose concentrations) were computed using standard least squares linear regressions analysis and six alternative regression techniques (weighted 1/x, 1/y, 1/x2, 1/y2 least squares linear, log/log least squares linear, and robust). The coefficient of determination (R2) and the coefficient of prediction (R2pred) values for standard curves and the computed values for validation points did not differ significantly among the seven methods. The lower limit of quantitation (LLQ) values obtained with all six of the alternative regression methods were significantly (P < .01) lower than the LLQ values obtained with least squares linear regression analysis. The lowest LLQ values were obtained with 1/x2 and 1/y2 weighting and were threefold to tenfold less than the values obtained with unweighted least squares linear regression analysis (P < .001). The authors conclude that alternative regression analysis techniques (especially 1/x2 and 1/y2 weighting) offer significant advantages for clinical pharmacology studies when concentration values being measured by HPLC are near the LLQ of the method determined by unweighted least squares linear regression analysis. In other situations, alternative forms of regression analysis had no significant advantages in our study.
Analysis of Variance↗
MULCOX: a computer program for the Cox regression analysis of multiple failure time variables.
MULCOX is a user-friendly FORTRAN program for the analysis of regression effects when individual study subjects may experience multiple events or failures. Each marginal distribution of the multivariate failure time variable is formulated by a Cox proportional hazards model. The maximum partial likelihood estimators of the regression parameters in these marginal models are approximately jointly normal. The MULCOX program estimates the marginal models as well as the joint covariance matrix. In addition, it implements several multivariate inference procedures. The program runs on both mainframe computers and microcomputers. The running time is quite acceptable even for large samples. A simple example is provided to illustrate the features of the program.
Mathematical Computing↗
Multivariate regression analysis of distance matrices for testing associations between gene expression patterns and related variables.
A fundamental step in the analysis of gene expression and other high-dimensional genomic data is the calculation of the similarity or distance between pairs of individual samples in a study. If one has collected N total samples and assayed the expression level of G genes on those samples, then an N x N similarity matrix can be formed that reflects the correlation or similarity of the samples with respect to the expression values over the G genes. This matrix can then be examined for patterns via standard data reduction and cluster analysis techniques. We consider an alternative to conventional data reduction and cluster analyses of similarity matrices that is rooted in traditional linear models. This analysis method allows predictor variables collected on the samples to be related to variation in the pairwise similarity/distance values reflected in the matrix. The proposed multivariate method avoids the need for reducing the dimensions of a similarity matrix, can be used to assess relationships between the genes used to construct the matrix and additional information collected on the samples under study, and can be used to analyze individual genes or groups of genes identified in different ways. The technique can be used with any high-dimensional assay or data type and is ideally suited for testing subsets of genes defined by their participation in a biochemical pathway or other a priori grouping. We showcase the methodology using three published gene expression data sets.
Animals↗
A statistics primer. Correlation and regression analysis.
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Adipose Tissue↗
Regression analysis of censored and truncated data: estimating reporting-delay distributions and AIDS incidence from surveillance data.
AIDS surveillance provides a vital source of information for health departments to assess the AIDS epidemic and to plan for future health-care needs. However, the use of surveillance data requires proper adjustments for the underreporting of AIDS cases caused by the delay in reporting diagnosed AIDS cases to the surveillance system. The statistical problem of adjusting for this underreporting concerns making inferences about an unobservable random sample of which only a portion is observed in a chronologic time interval defined by the analysis. Most regression methods for making inferences using right-truncated data employ a reverse-time hazard function, which requires that the observed data be transformed so that methods for left-truncated data can be applied. In this paper, we discuss fitting regression models to data that can be truncated and even censored in arbitrary intervals. The proposed methodology was applied to the national AIDS surveillance data provided by the Centers for Disease Control to analyze the trend of delays over chronologic time and variation among different geographic regions as well as across risk groups.
Acquired Immunodeficiency Syndrome↗
Application of regression analysis to examination of degree of loss of hearing.
The present study is an attempt to apply analysis of regression for the purposes of evaluation of loss of hearing. This method consists in calculating equations of regression for relation between the age of the examined people and the degree of elevation of the hearing threshold for various frequencies. The slope of the regression line allows to conclude about the degree of damage to hearing. Practical application of this method was shown with an example of a study on the status of hearing in workers of several manufacturing departments of a pottery plant.
Adult↗
The stochastic regression analysis as a tool in ecotoxicological QSAR studies.
Correspondence factor analysis (CFA) was used in conjunction with linear regression analysis to examine the structure-activity relationships of 50 benzene derivatives tested on Pimephales promelas. From nine molecular descriptions (numbers of C, H, O, N, Br, Cl, NO2, OH, and NH2 included in the molecules), CFA made it possible to define five new independent variables which were introduced in a stepwise regression analysis procedure to describe the acute toxicity (96-h LC50) of the aromatic compounds. The model log 1/C = -0.727F1 + 1.248F3 + 4.052 (r = 0.918; s = 0.270) is more relevant to describe the ecotoxicological behavior of the studied compounds on the fathead minnow than that obtained with principal components (log 1/C = 0.151 PC1 -0.271 PC2 + 4.124; r = 0.737; s = 0.460). The heuristic potency of this particular statistical analysis, which is called stochastic regression analysis, is discussed in detail.
Animals↗
Interpretation of research data: regression analysis.
The types of problems that can be analyzed with regression analysis, and interpretation of the resulting summary statistics, are discussed. Linear and multiple regression models, regression coefficients are described. Regression analysis can answer questions about the existence and strength of relationships and the relative importance of independent variables, and can forecast the outcome from changes in the values of independent variables. Multivariate regression analysis can detect the contribution of each of several independent variables on the dependent variable.
Humans↗
Determination of species- and laboratory-related interpretive breakpoints for doxycycline susceptibility testing using single-strain regression analysis.
Single-strain Regression Analysis (SRA) was performed for doxycycline on a total of 68 bacterial strains representing 16 different species. Species- and laboratory-related zone diameter breakpoints were determined and compared with histograms of zone diameter values obtained from 942 routine susceptibility tests. Calculated breakpoints were similar within individual species. When considering the homogeneity of susceptibility groups within bacterial species, the calculated breakpoints gave rise to relatively few interpretive errors. In contrast, general breakpoints for doxycycline as recommended by the Swedish Reference Group (SRG) (R less than = 20 mm and S greater than = 26 mm) would give rise to a high proportion of false interpretations in the present laboratory. Fifty-three per cent of H.influenzae strains would have been assigned to the wrong susceptibility group. For E.coli and K.pneumoniae, 22 and 35 per cent, respectively, would have been erroneously categorized using SRG breakpoints. E.cloacae and E.aerogenes would have been assigned another category in 39 and 50 per cent, respectively. The procedure for setting species-specific and laboratory-related interpretive breakpoints is described. Determination of species- and laboratory-related interpretive breakpoints using SRA provides a new approach towards improved accuracy of disc-diffusion susceptibility testing.
Doxycycline↗
Factors predisposing to healing complications after internal fixation of femoral neck fracture. A stepwise logistic regression analysis.
A stepwise logistic regression analysis was made to assess the influence of various factors on the rate of healing complications after femoral neck fracture. A prospective series comprising 101 patients with fresh fractures treated by closed reduction and internal fixation was included in a roentgenographic follow-up study. The single most important factor was the quality of reduction, followed by the type of fracture, and the position of the internal fixation material. Age, gender, and type of internal fixation device (three screws or three nails) were not found to influence the healing complication rate. The predicted probability of a healing complication for different combinations of the three most important factors ranged from 0.05 to 0.99. The highest value was found for the combination Garden Type IV fracture, which had unacceptable reduction and position of the internal fixation material. The results show that failure to achieve adequate reduction should be a strong argument in favor of primary hip arthroplasty.
Adult↗
Regression analysis with multiplicative and time-varying additive regression coefficients with examples from breast and colon cancer.
Regression analysis may be used to simplify the representation of mortality rates when there are many significant prognostic covariates or to adjust for confounding effects. The principal request of the regression model in this range of use is to have unbiased parameter estimates. A model with constant multiplicative and time-varying additive regression coefficients is discussed. The model allows some covariate effects to be multiplicative while allowing others to have a time-varying additive effect. Thus, it is a mix of classical Cox regression and Aalen's additive risk model. A major characteristic of cancer mortality rates, in contrast to general mortality rates, is that hazard rates, after a potentially initial increase, decrease, although not always tending to zero. Cancer diseases, like breast and colon cancer, have significantly increased cause-specific mortality rates even 20 years after diagnosis. Another major feature in cancer survival analysis is that many covariate effects are time-varying. Some covariate effects, like age at diagnosis, may only be significant for a limited time after diagnosis. Furthermore, some treatment procedures may initially decrease the mortality, while the long-term effect may be opposite. A third issue is that average covariate effects are very often not multiplicative. Estimation is carried out iteratively; the cumulative additive regression functions are estimated non-parametrically using a least-squares method and the multiplicative parameters are estimated from the partial likelihood. The method is applied on 3201 female breast cancer and 1372 male colon cancer patients.
Adult↗
Determination of interpretive breakpoints for ceftazidime disc-diffusion susceptibility testing using single-strain regression analysis.
Interpretive breakpoints for ceftazidime disc-diffusion susceptibility testing were determined using single-strain regression analysis (SRA). Regression lines were determined for a total of 58 strains representing 15 species, from inhibition zone diameters obtained for discs containing six different ceftazidime concentrations. Statistical analysis for excluding non-linearity of test-results was performed. A minimum of five tests on consecutive days was required for maximal precision of regression analysis according to the SRA-method. Calculated regression lines showed similarities within individual and groups of bacterial species. A minimum of five strains could be used to represent these groups. Interpretive breakpoints according to recommended MIC-limits were determined for each species taking into consideration confidence limits for zone correlates of MIC-values. Single-strain regression analysis for the determination of interpretive breakpoints for ceftazidime disc-diffusion susceptibility testing in individual laboratories.
Ceftazidime↗
[A study of the clinical factors which have the greatest effect on bronchial hyperresponsiveness in atopic asthma by multiple regression analysis].
We studied the clinical factors which have the greatest effect on bronchial hyperresponsiveness, with 37 atopic asthma patients (23 males and 14 females). They were from 13 to 59 years old. We measured the control value of the respiratory conductance (Grs.cont), the minimum dose of methacholine (bronchial sensitivity, Dmin), the linear slope of the Grs (= 1/Rrs) decreased (bronchial reactivity, SGrs) and SGrs/Grs.cont by the "Astograph" method (Chest 80, 600, 1981). Statistical analysis was performed by multiple regression analysis. Grs.cont, log Dmin, SGrs and SGrs/Grs.cont were regarded as objective variables. Age, onset age of asthma, period of disease, smoking history, family history of atopy, serum IgE, blood eosinophil counts, positive skin test counts, FEV1.0% and type of asthma attack (perennial or seasonal) were regarded as explanatory variables. The results were as follows: 1) The explanatory variable which showed the highest partial correlation coefficients, was the type of asthma attack in multiple regression analysis of Grs.cont and log Dmin (p < 0.05, p < 0.05). 2) Grs.cont of perennial asthma attack (0.247 +/- 0.064) was significantly lower than that of seasonal attack (0.318 +/- 0.097) (p < 0.02). Log Dmin of perennial asthma attack (-0.837 +/- 0.457) was significantly lower than that of seasonal attack (-0.254 +/- 0.429) (p < 0.005). Therefore in mild atopic asthma, the clinical factor which has the greatest effect on bronchial hyperresponsiveness is the type of asthma attack. We conclude that the existence of perennial asthma attacks is mostly related to increased bronchial hypersensitivity.
Adolescent↗
Advantages of examining multicollinearities in regression analysis.
In this paper a regression analysis is performed with data on spinal cord injuries in order to demonstrate the benefits of determining which, if any, multicollinearities are present in prediction data. Existing multicollinearities are shown to be useful both in determining characteristics of the sampled population as well as explaining possible erratic behavior of variable selection procedures. Latent root regression is performed on the data to illustrate one method of using biased regression techniques to incorporate knowledge of multicollinearities in developing prediction equations.
Humans↗
Pelvic relaxation and associated risk factors: the results of logistic regression analysis.
BACKGROUND: To determine the possible risk factors in our population. METHODS: From 250 patients attending our clinic 28 patients with pelvic relaxation were the study group and the rest, 222 in all, were the control group. RESULTS: Age, marriage period, parity and number of abortus in pelvic relaxation group are found to be significantly higher with univariate analysis. With logistic regression analysis menopause, grandmultiparity, abortus (two or more), home deliveries, history of macrosomic infant (4500 gr. or more), deliveries without episiotomy and laceration of uterine cervix are found to be risk factors for pelvic relaxation. CONCLUSIONS: Good family planning programs to reduce grandmultiparity and unnecessary curettage for undesired pregnancies, preventing harmful home deliveries by inexperienced people, and fearless usage of episiotomy in difficult deliveries are necessary to prevent pelvic relaxation.
Abortion, Induced↗
Is there a suicidality syndrome independent of specific major psychiatric disorder? Results of a split half multiple regression analysis.
Biological findings such as low 5-HIAA levels in cerebrospinal fluid (CSF) in suicidal patients compared to non-suicidal patients independent of the type of psychiatric disorder indicate a broad basis for suicidality. It is therefore important to ask whether a suicidality syndrome can be delineated on a phenomenological level, and whether it is independent of specific major psychiatric disorders which are otherwise considered to be aetiologically different. This paper reports on a study of 2383 schizophrenic and 1920 depressive unselected patients with and without suicidality. They were assessed during the first 24 h after admission to a psychiatric in-patient facility using a comprehensive psychopathological assessment (AMDP system). Using multiple variance analysis and logistic regression analysis based on single symptoms, for both suicidal and non-suicidal patients it was shown that a suicidality syndrome independent of the underlying illness can be delineated. In schizophrenia as well as in major affective disorders it was found that hopelessness, ruminative thinking, social withdrawal and lack of activity are core symptoms of this suicidal syndrome. The finding of a suicidality syndrome, not associated with a specific major affective disorder, indicates the need to identify this syndrome, which should be seen as an independent dimension and diagnosed separately, and not regarded merely as a secondary symptom of major psychiatric disorders, particularly affective disorders.
Adult↗
Quantification of dark adaptation dynamics in retinitis pigmentosa using non-linear regression analysis.
PURPOSE: Non-linear regression analysis was used to determine dark adaptation indices in people with retinitis pigmentosa and in control subjects. METHODS: Dark adaptation data were collected for 13 people with retinitis pigmentosa and 21 controls using the Goldmann-Weekers Dark Adaptometer. Data were analysed using an exponential non-linear regression model and dark adaptation indices derived. The results were compared to age-related values. RESULTS: The mean cone threshold of the group with RP (4.73 +/- 0.19 log units) was significantly greater than that found in the control group (3.69 +/- 0.12 log units). The rate of cone dark adaptation in the RP group was not significantly different from that of the control group. The a break in the RP group (6.46 +/- 0.70 minutes) was delayed when compared to the control group (4.29 +/- 0.21 minutes) and the rate of rod dark adaptation in the RP group was slower (10 +/- 2 per cent per minute) than that of the control group (15 +/- 1 per cent per minute). CONCLUSIONS: This study has shown that a relatively simple data analysis can provide a more quantitative and intuitive description of dark adaptation rates in people with retinal disease. This technique will enable more effective use of dark adaptometry as a supplement to objective electrophysiology, when monitoring people with retinitis pigmentosa.
Adult↗