Results 71 to 80 of about 3,588,558 (310)
Using Quantile Regression for Duration Analysis [PDF]
Quantile regression methods are emerging as a popular technique in econometrics and biometrics for exploring the distribution of duration data. This paper discusses quantile regression for duration analysis allowing for a flexible specification of the ...
Wilke, Ralf A., Fitzenberger, Bernd
core
ABSTRACT Introduction Nephrogenic rests (NRs) and nephroblastomatosis (NBM) are precursor lesions for development of Wilms tumor (WT). Their association with the risk of relapse has not been properly assessed, partly due to misunderstanding of their diagnostic criteria and terminology.
Gordan M. Vujanić +5 more
wiley +1 more source
ABSTRACT Background Sickle cell disease (SCD) has undergone major changes in the last decades. Its prevalence has been steadily increasing and numerous advances have been made in the management of the disease. However, the effect in real‐life setting of these major changes is unknown, particularly in a Canadian environment. Procedure We aimed to assess
Maude Cigna +16 more
wiley +1 more source
Least squares estimation of regression coefficients of singular random fields observed on a sphere [PDF]
We present some results on the rate of convergence to the normal law of the least square estimates of the regression coefficient of random fields with long range dependence observed on a ...
Anh, Vo +5 more
core +1 more source
ABSTRACT Background Chronic micro‐inflammation in patients with end‐stage renal disease (ESRD) is a significant driver of cardiovascular complications and diminished quality of life. While standard hemodialysis (SHD) effectively manages small‐molecule clearance, its ability to remove medium‐to‐large uremic toxins—the primary catalysts of systemic ...
Hongwei Zuo +5 more
wiley +1 more source
Boosting Ridge Regression [PDF]
Ridge regression is a well established method to shrink regression parameters towards zero, thereby securing existence of estimates. The present paper investigates several approaches to combining ridge regression with boosting techniques.
Binder, Harald, Tutz, Gerhard
core +1 more source
Regression without regrets –initial data analysis is a prerequisite for multivariable regression
Statistical regression models are used for predicting outcomes based on the values of some predictor variables or for describing the association of an outcome with predictors.
Georg Heinze +7 more
doaj +1 more source
ABSTRACT Introduction This final analysis of a multicenter, prospective postmarketing surveillance study evaluated the safety of daprodustat in patients with chronic kidney disease anemia in routine clinical practice in Japan. Methods Patients who initiated daprodustat between September 2020 and July 2022 were registered.
Tadao Akizawa +7 more
wiley +1 more source
Bayesian Geoadditive Seemingly Unrelated Regression [PDF]
Parametric seemingly unrelated regression (SUR) models are a common tool for multivariate regression analysis when error variables are reasonably correlated, so that separate univariate analysis may result in inefficient estimates of covariate effects. A
Steiner, Winfried J. +3 more
core +1 more source
Regression to the mean in regression discontinuity design: bias and sensitivity analysis
When making causal inferences from observational data, researchers must consider the effects of confounding. In a regression discontinuity design (RDD), individuals receive a treatment based on whether they score below or above a threshold value measured
Karmakar Bikram
doaj +1 more source

