Population size, density, urbanization and the division of labor.
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Americas↗
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Results for “Statistical Regression”
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Why do phase III trials of promising heart failure drugs often fail? The contribution of "regression to the truth".
There has been considerable recent disappointment with the failure of a number of major new pharmacological strategies for the treatment of chronic heart failure. In turn, there has been much speculation as to why trials of these therapies have not shown benefit. Among a number of plausible and scientifically valid reasons, consideration should be afforded to the potential contribution of "regression to the truth." Regression to the truth derives from the biological concept of regression to the mean, whereby random fluctuations in a biological variable occur over time, such that the true value of the variable is approached with repeated measurements. This same concept can be applied to clinical trial programs for new drugs for heart failure. Because only strongly positive trials generally go on to phase III testing, and some of these early phase studies are positive by chance alone, on retesting in phase III the results are very likely not be as strongly positive. Numerous examples of regression to the truth apply for trials of heart failure therapies, as well as in other areas. A major concern is how to minimize negative outcomes in phase III trials. One approach is to perform major rigorous phase II testing. Alternatively, avoidance of phase II testing will minimize "regression to the truth" because there are no data in phase II from which regression might occur. However, this approach does not obviate the need for an evaluation process in the selection of candidate agents (and their appropriate dose) in order to proceed to definitive testing.
Cardiotonic Agents↗
Limitations of angiography for analyzing coronary atherosclerosis progression or regression.
PURPOSE: To analyze the utility and limitations of serial coronary angiography for determining atherosclerosis progression and regression. DATA SOURCES: A MEDLINE search of the English-language literature (1966 to January 1994) using the keywords atherosclerosis regression, atherosclerosis progression, lipid reduction therapy, and coronary angiography. STUDY SELECTION: Selected articles on the effects of cholesterol reduction and lifestyle modification on angiographic coronary artery disease, on the animal models of atherosclerosis progression and regression, and on the limitations of coronary angiography. DATA EXTRACTION: Independent extraction by two authors. RESULTS: Although several studies have reported that the rate of atherosclerosis progression, defined by serial coronary angiography, can be reduced and that luminal diameter can be improved somewhat by aggressive lipid modification, the reported changes are small (0.3 mm or 10% change) and have required a prolonged study duration (range, 1 to 10 years). More importantly, angiography simply does not measure atherosclerosis and cannot assess lesion composition. Angiography also underestimates the extent of atherosclerosis, especially in angiographically normal segments. In addition, difficulties with data acquisition, such as substantial variabilities in serial measurements of percent diameter stenosis and minimal luminal diameters, require large sample sizes to show statistically significant regression, even with computerized quantification. CONCLUSIONS: Given its current limitations, serial coronary angiography is not a satisfactory means of detecting atherosclerosis progression or regression.
Anticholesteremic Agents↗
Dysmenorrhea and use of oral contraceptives in adolescent women attending a family planning clinic.
OBJECTIVES: This study examined the prevalance of dysmenorrhea in female adolescents and the effect of experiencing a reduction in dysmenorrhea on oral contraceptive use. STUDY DESIGN: This was a prospective panel study in which 308 adolescent women at an inner-city family planning clinic were interviewed about their experiences with dysmenorrhea and their oral contraceptive use at three points in time over a 6-month period. A chi 2 test and multiple logistic regression analysis were done. RESULTS: The overall prevalence of dysmenorrhea in this population was 79.6%; 18.2% reported severe dysmenorrhea. Those who had severe dysmenorrhea and also experienced the reduction of dysmenorrhea as a result of oral contraceptives were eight times more likely to be consistent oral contraceptive users (p less than or equal to 0.02). CONCLUSIONS: It is important to screen female adolescents for dysmenorrhea, provide them with information about the beneficial side effects of oral contraceptives, and follow up these young women to make sure they are experiencing the alleviation of their symptoms.
Adolescent↗
Accident prediction models for roads with minor junctions.
The purpose of this study was to develop and validate a method for predicting expected accidents on main roads with minor junctions where traffic counts on the minor approaches are not available. The study was based on data for some 3800 km of highway in the U.K. including more than 5000 minor junctions. The highways consisted of both single and dual-carriageway roads in urban and rural areas. Generalized linear modelling was used to develop regression estimates of expected accidents for six highway categories and an empirical Bayes procedure was used to improve these estimates by combining them with accident counts. Accidents on highway sections were shown to be a non-linear function of exposure and minor junction frequency. For the purposes of estimating expected accidents, while the regression model estimates were shown to be preferable to accident counts, the best results were obtained using the empirical Bayes method. The latter was the only method that produced unbiased estimates of expected accidents for high-risk sites.
Accidents, Traffic↗
A regression model for longitudinal change in the presence of measurement error.
PURPOSE: The analysis of change in measured variables has become quite popular in studies where data are collected repeatedly over time. The authors describe some of the potential pitfalls in the analysis of change when the variable for change is measured with error. They show that regression analysis is often biased, possibly leading to erroneous results. METHODS: A simple method to correct for measurement error bias in regression models that model change is presented. RESULTS AND CONCLUSIONS: The two examples illustrate how measurement error can adversely affect an analysis. The bias-corrected approach yields valid results.
Aged↗
Social and geographical risk factors in Helicobacter pylori infection.
A correlation between childhood crowding and the later development of gastric cancer has been demonstrated by Barker and colleagues, who proposed that the relationship was the consequence of infection by an organism such as Helicobacter pylori. In order to test this hypothesis the presence of IgG antibodies to H. pylori in sera from blood donors in North Wales has been investigated. During donation sessions, donors answered questions relating to social conditions and domicile in childhood (at age 10 years) and adult life (the preceding 2 years). A stepwise logistic regression analysis of the data demonstrated significant independent relationships between seropositivity and the following factors: sharing a bed in childhood, housing density, locality of birth, adult social class and age.
Adult↗
Effect of decreased retinal illumination on simultaneously recorded pattern electroretinograms and visual-evoked potentials.
Sixteen normal subjects and three patients with optic neuritis were studied to determine the effect of decreased retinal illumination on simultaneously recorded pattern electroretinograms (PERG) and visual-evoked potentials (VEP). Using neutral-density filters (NDF), it was found that linear modeling is an excellent fit for VEP/PERG amplitudes and latencies as log functions of retinal illumination, both for individual eyes and averages of pooled data. Within narrow statistical limits, regression slopes show that mean PERG B-wave and VEP P100 latencies are affected almost identically by decreased illumination, leaving the mean retinocortical time (RCT) virtually unchanged. However, mean B-wave amplitude was greatly reduced at retinal illuminations at which P100 amplitude was unaffected. Of clinical significance was that these latency and amplitude effects were found in each eye tested, whether normal or pathologic. In particular, the RCT in normal subjects was never found to be statistically abnormal due to decreased retinal illumination, and it faithfully represented the optic nerve lesion in the patients with optic neuritis. This result was applied to a population of eight patients with uncomplicated cataracts. The significance of these results is discussed.
Adolescent↗
The detection of peaks in luteinizing hormone secretion.
Fluctations in luteinizing hormone are believed to consist of irregularly spaced sharp increases separated by periods of exponential decay. A simple method is presented for analysing such fluctuations when the data consist of uniformly sampled observations of hormone. Specific allowance for the exponential decay in the absence of pulses is made via a time series model before assessing the number and extent of pulses. All calculations are done using MINITAB regression programs. The results have been compared with those obtained by three established models and are in general agreement.
Activity Cycles↗
A statistical investigation of amphiphilic properties of C-terminally anchored peptidases.
A number of DD-peptidases have been reported to interact with the membrane via C-terminal amphiphilic alpha-helices, but experimental support for this rests with a few well-characterized cases. These show the C-terminal interactions of DD-carboxypeptidases to involve high levels of membrane penetration, DD-endopeptidases to involve membrane surface binding and class C penicillin-binding proteins to involve membrane binding with intermediate properties. Here, we have characterized C-terminal alpha-helices from each of these peptidase groups according to their amphiphilicity, as measured by mean , and the corresponding mean hydrophobicity, . Regression and statistical analyses showed these properties to exhibit parallel negative linear relationships, which resulted from the spatial ordering of alpha-helix amino acid residues. Taken with the results of compositional and graphical analyses, our results suggest that the use of C-terminal alpha-helices may be a universal feature of the membrane anchoring for each of these groups of DD-peptidases. Moreover, to accommodate differences between these mechanisms, each group of C-terminal alpha-helices optimizes its structural amphiphilicity and hydrophobicity to fulfil its individual membrane-anchoring function. Our results also show that each anchor type analysed requires a similar overall balance between amphiphilicity for membrane interaction, which we propose is necessary to stabilize their initial membrane associations. In addition, we present a methodology for the prediction of C-terminal alpha-helical anchors from the classes of DD-peptidases analysed, based on a parallel linear model.
Amino Acid Sequence↗
Methods of ordinal classification applied to medical scoring systems.
Scoring systems are used in nearly all fields of medicine for evaluation of the state of a disease. The prediction performance of scoring systems with respect to an ordinal outcome scale is investigated, based on grouped continuous logistic models as well as on an extension of the stereotype logistic regression model. The latter is a canonical approach, which allows assessment of properties of outcome categories such as partial and total ordering, distinguishability and allocatability. The approach is applied to a data set of patients with injuries of the head.
Cerebral Arteries↗
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↗
Apparent diffusion coefficient of intervertebral discs related to matrix composition and integrity.
While tremendous work has been performed to characterize degenerative disc disease through gross morphologic, biochemical, and histologic grading schemes, the development of an accurate and noninvasive diagnostic tool is required to objectively detect changes in the matrix with aging and disc degeneration. In the present study, quantitative magnetic resonance was used to determine if the quality of the nutritional supply to the intervertebral disc at various ages and levels of degeneration could be assessed through measurement of the apparent diffusion coefficients (ADCs). Modifications of the nucleus pulposus matrix content, specifically of water and glycosaminoglycan contents, with age and disc degeneration, were reflected in correlating changes in the ADCs. From unforced stepwise linear regression analyses, relations were established showing that decreases in glycosaminoglycan or water contents in the nucleus pulposus resulted in direct decreases in the ADCs. Relations obtained for the ADCs of the nucleus pulposus were direction dependent, in conformity with the anisotropic diffusion in the intervertebral discs. Changes in matrix integrity, as evidenced by the percentage of denatured collagen, were also detected in the nucleus pulposus with a low positive correlation to the ADC along the height of the disc and an inverse statistically significant regression to the ADC along the anterior to posterior axis of the disc. Correlations between the matrix content and integrity of the annulus fibrosus and its ADCs were not as evident, with only the ADC in the lateral direction of the disc of the anterior annulus fibrosus able to reflect changes in matrix content. The information obtained by the ADCs, particularly of the nucleus pulposus, can potentially be used in combination with quantitative T1, T2, and MT parameters to noninvasively obtain a quantitative assessment of the disc matrix composition and structural integrity.
Adolescent↗
Socio-economic determinants of fertility in some countries of Asia.
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Asia↗
Assessment of CSO loads--based on UVIVIS-spectroscopy by means of different regression methods.
The use of UV/VIS-spectroscopy for water quality measurements is based on the solution of the correlation between the surrogate parameter absorbance and the resulting equivalence parameters. The coherence of absorbance and equivalence parameters (CODtot, CODsol, TSS) is solved in this paper with different regression methods. The correlation of absorbance and concentrations are analysed based on linear regression methods, model tree regressions, multivariate regression methods and support vector machines using sequential minimal optimisation algorithm. For this purpose the regression methods are calibrated on three 24hours measurement campaigns of a combined sewer measurement station situated in the combined sewer overflow chamber in Graz (Austria). The online measurement station has been conveying data for more than 2 1/2 years up to now. Finally, the load calculation based on the different regression methods and its comparison demonstrate that an apparently complex model does not inevitably lead to accurate concentration values due to possible model overfitting. Hence, the paper points out the possibilities and the drawbacks of spectroscopy measuring in sewers and the arising concentration values.
Drainage, Sanitary↗
Estimating regression models with unknown break-points.
This paper deals with fitting piecewise terms in regression models where one or more break-points are true parameters of the model. For estimation, a simple linearization technique is called for, taking advantage of the linear formulation of the problem. As a result, the method is suitable for any regression model with linear predictor and so current software can be used; threshold modelling as function of explanatory variables is also allowed. Differences between the other procedures available are shown and relative merits discussed. Simulations and two examples are presented to illustrate the method.
Bronchitis↗
On the efficacy of the rank transformation in stepwise logistic and discriminant analysis.
We have evaluated the performance of four stepwise variable selection procedures commonly used in medical and epidemiologic research. The four procedures are discriminant and logistic regression and their rank transformed versions, where the independent variables are replaced by their ranks. We generated, by computer, data for two groups from several distributions with a variety of sample sizes and covariance matrices. The two ranking procedures each increased the chance of correctly selecting those variables related to group membership for data generated from log-normal or contaminated distributions. For normally distributed data the ranking procedure had little effect on variable selection. Rank transformed discriminant analysis and rank transformed logistic regression were equally effective in selecting variables when sample sizes exceeded 100. Rank transformed discriminant analysis was superior for smaller data sets. We discuss the implications of the results of this study for clinical and epidemiologic research.
Case-Control Studies↗
Postwar fertility cycles and the Easterlin hypothesis: a life-cycle approach.
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Demography↗