Results 91 to 100 of about 2,094,340 (297)
Examining the Reliability of Logistic Regression Estimation Software [PDF]
Research Methods/ Statistical Methods,
Bergtold, Jason S. +2 more
core +1 more source
Sex Hormones Associate With Amyotrophic Lateral Sclerosis Risk and Survival
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Amyotrophic lateral sclerosis (ALS) risk differs by sex and age, implicating sex hormones as potential modifiers. This study examined plasma levels of biologically active sex hormones and their association with ALS odds and survival in cases (females n = 131, males n = 189) and controls (females n = 138, males n = 150) from the University of ...
Stephen A. Goutman +5 more
wiley +1 more source
BLESS: bagged logistic regression for biomarker identification
Frontiers in GeneticsThe traditional single nucleotide polymorphism (SNP)-wise approach in genome-wide association studies is focused on examining the marginal association between each SNP with the outcome separately and applying multiple testing adjustments to the resulting
Kyle Gardiner, Xuekui Zhang, Li Xing
doaj +1 more source
Bayesian multiple logistic regression for case-control GWAS.
PLoS Genetics, 2018 Genetic variants in genome-wide association studies (GWAS) are tested for disease association mostly using simple regression, one variant at a time. Standard approaches to improve power in detecting disease-associated SNPs use multiple regression with ...
Saikat Banerjee +3 more
doaj +1 more source
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Background Myasthenia gravis (MG) is an autoimmune disorder characterized by antibody‐mediated complement activation. Efgartigimod, a neonatal Fc receptor (FcRn) antagonist, is approved for treating generalized MG (gMG). However, its modulatory effects on upstream innate and adaptive immune cells remain largely unexplored.
Lei Jin +11 more
wiley +1 more source
Missing covariates in logistic regression, estimation and distribution selection. [PDF]
We derive explicit formulae for estimation in logistic regression models where some of the covariates are missing. Our approach allows for modeling the distribution of the missing covariates either as a multivariate normal or multivariate t-distribution.
Claeskens, Gerda, Consentino, Fabrizio
core
Bayesian Estimation Improves Prediction of Outcomes After Epilepsy Surgery
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT We estimated the statistical power of studies predicting seizure freedom after epilepsy surgery. We extracted data from a Cochrane meta‐analysis. The median power across all studies was 14%. Studies with a median sample size or less (n ≤ 56) and a statistically significant result exaggerated the true effect size by a factor of 5.4, while the ...
Adam S. Dickey +4 more
wiley +1 more source
Multi-category diagnostic accuracy based on logistic regression
Statistical Theory and Related Fields, 2017 We provide a detailed review for the statistical analysis of diagnostic accuracy in a multi-category classification task. For qualitative response variables with more than two categories, many traditional accuracy measures such as sensitivity ...
Jialiang Li +2 more
doaj +1 more source
Ordinal logistic regression [PDF]
American Journal of Orthodontics and Dentofacial Orthopedics, 2018 Despina, Koletsi, Nikolaos, Pandis
openaire +2 more sources