Rank estimates and asymptotic linearity in regression parameters

1999 ◽  
pp. 358-382
Author(s):  
Jaroslav Hájek ◽  
Zbyněk Šidák ◽  
Pranab K. Sen
Molecules ◽  
2021 ◽  
Vol 26 (12) ◽  
pp. 3682
Author(s):  
Katarína Vizárová ◽  
Izabela Vajová ◽  
Naďa Krivoňáková ◽  
Radko Tiňo ◽  
Zdenko Takáč ◽  
...  

The surface pH is a critical factor in the quality and longevity of materials and products. Traditional fast colorimetric pH detection-based tests such as water quality control or pregnancy tests, when results are determined by the naked eye, cannot provide quantitative values. Using standard pH papers, paper-printed comparison charts, or colorimetric microfluidic paper-based analytical devices is not suitable for such technological applications and quality management systems (QMSs) where the particular tested material should contain a suitable indicator in situ, in its structure, either before or after the process, the technology or the apparatus that are being tested. This paper describes a method based on the combination of impregnation of a tested material with a pH indicator in situ, its exposure to a process of technology whose impact on pH value is to be tested, colorimetric pH measurement, and approximation of pH value using derived pH characteristic parameters (pH-CPs) based on CIE orthogonal and cylindrical color variables. The hypotheses were experimentally verified using the methyl red pH indicator, impregnating the acid lignin-containing paper, and preparing a calibration sample set with pH in the range 4 to 12 using controlled alkalization. Based on the performed measurements and statistical evaluation, it can be concluded that the best pH-CPs with the highest regression parameters for pH are √∆E, ln (a),√∆H (ab), a/L, h/b and ln (b/a). The experimental results show that the presented method allows a good estimation of pH detection of the material surfaces.


2014 ◽  
Vol 891-892 ◽  
pp. 1639-1644 ◽  
Author(s):  
Kazutaka Mukoyama ◽  
Koushu Hanaki ◽  
Kenji Okada ◽  
Akiyoshi Sakaida ◽  
Atsushi Sugeta ◽  
...  

The aim of this study is to develop a statistical estimation method of S-N curve for iron and structural steels by using their static mechanical properties. In this study, firstly, the S-N data for pure iron and structural steels were extracted from "Database on fatigue strength of Metallic Materials" published by the Society of Materials Science, Japan (JSMS) and S-N curve regression model was applied based on the JSMS standard, "Standard Evaluation Method of Fatigue Reliability for Metallic Materials -Standard Regression Method of S-N Curve-". Secondly, correlations between regression parameters and static mechanical properties were investigated. As a result, the relationship between the regression parameters and static mechanical properties (e.g. fatigue limit E and static tensile strength σB) showed strong correlations, respectively. Using these correlations, it is revealed that S-N curve for iron and structural steels can be predicted easily from the static mechanical properties.


Author(s):  
Marco Doretti ◽  
Martina Raggi ◽  
Elena Stanghellini

AbstractWith reference to causal mediation analysis, a parametric expression for natural direct and indirect effects is derived for the setting of a binary outcome with a binary mediator, both modelled via a logistic regression. The proposed effect decomposition operates on the odds ratio scale and does not require the outcome to be rare. It generalizes the existing ones, allowing for interactions between both the exposure and the mediator and the confounding covariates. The derived parametric formulae are flexible, in that they readily adapt to the two different natural effect decompositions defined in the mediation literature. In parallel with results derived under the rare outcome assumption, they also outline the relationship between the causal effects and the correspondent pathway-specific logistic regression parameters, isolating the controlled direct effect in the natural direct effect expressions. Formulae for standard errors, obtained via the delta method, are also given. An empirical application to data coming from a microfinance experiment performed in Bosnia and Herzegovina is illustrated.


2000 ◽  
Vol 124 (11) ◽  
pp. 1599-1607 ◽  
Author(s):  
Ian R. Wanless ◽  
Eisuke Nakashima ◽  
Morris Sherman

Abstract Context.—Cirrhosis is widely regarded as being irreversible. Recent studies have demonstrated that fibrosis may decrease with time in humans and experimental animals if the disease activity becomes quiescent. The histologic appearance of regressing cirrhosis in the human has not been described in detail. Objectives.—To define histologic parameters that indicate regression of cirrhosis and to provide an interpretation of how regression occurs from a histologic point of view. Design.—A patient who underwent a series of biopsies that showed apparent regression of hepatitis B cirrhosis is presented. In addition, 52 livers removed at transplantation having cirrhosis or incomplete septal cirrhosis were graded for histologic parameters that suggest progression or regression of fibrosis. Progression parameters were steatohepatitis, inflammation, bridging necrosis, and piecemeal necrosis. The regression parameters (collectively called the hepatic repair complex) were delicate perforated septa, isolated thick collagen fibers, delicate periportal fibrous spikes, portal tract remnants, hepatic vein remnants with prolapsed hepatocytes, hepatocytes within portal tracts or splitting septa, minute regenerative nodules, and aberrant parenchymal veins. Results and Conclusions.—Regression parameters were found in all livers and were prominent in the majority. Livers with micronodular cirrhosis, macronodular cirrhosis, and incomplete septal cirrhosis demonstrate a histologic continuum. A continuum of regressive changes was also seen within individual livers. These appearances allow one to understand visually how fibrous regions of hepatic parenchyma can be returned toward a normal appearance. Many examples of incomplete septal cirrhosis could be the product of regressed cirrhosis.


2018 ◽  
Vol 28 (10-11) ◽  
pp. 3363-3391 ◽  
Author(s):  
Philip S Rosenberg

We develop a new age-period-cohort model for cancer surveillance research; the theory and methods are broadly applicable. In the new model, cohort deviations are weighted to account for the variable number of periods that each cohort is observed. Weighting ensures that the fitted rates can be naturally expressed as a function of age × a function of period × a function of cohort. Furthermore, the age, period, and cohort deviations are split into orthogonal quadratic components plus higher-order terms. These decompositions enable powerful combination significance tests of first- and second-order age, period, and cohort effects. The regression parameters of the orthogonal quadratic polynomials (global curvatures) quantify how fast on average the trends in the rates are changing. Importantly, the global curvature for cohort determines the least squares slope of the expected annual percentage changes by age group versus age (local drifts), thereby providing a powerful one-degree-of-freedom test of age-period interactions. We introduce new estimable functions, including age gradients that quantify the rate of change of the longitudinal and cross-sectional age curves at each attained age, and gradient shifts that quantify how the cross-sectional age trend varies by period. We illustrate the new model using nationally representative multiple myeloma incidence. Comprehensive proofs are given in technical appendices. We provide an R package.


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