Finding factors influencing risk: comparing Bayesian stochastic search and standard variable selection methods applied to logistic regression models of cases and controls.
about
Air toxics and birth defects: a Bayesian hierarchical approach to evaluate multiple pollutants and spina bifidaPooling dietary data using questionnaires with open-ended and predefined responses: implications for comparing mean intake or estimating odds ratios.Variable selection method for quantitative trait analysis based on parallel genetic algorithm.Small sample properties of rare variant analysis methods.Investigating multiple candidate genes and nutrients in the folate metabolism pathway to detect genetic and nutritional risk factors for lung cancer.Artificial neural network models for prediction of cardiovascular autonomic dysfunction in general Chinese populationUsing a Bayesian hierarchical model for identifying single nucleotide polymorphisms associated with childhood acute lymphoblastic leukemia risk in case-parent triads.A simple Chinese risk score model for screening cardiovascular autonomic neuropathy.Using Ascertainment for Targeted Resequencing to Increase Power to Identify Causal Variants.Symptom clusters of pain, depressed mood, and fatigue in lung cancer: assessing the role of cytokine genesNorthern Shanghai Study: cardiovascular risk and its associated factors in the Chinese elderly-a study protocol of a prospective study design.Bayesian Variable Selection under the Proportional Hazards Mixed-effects Model.Bovine Tuberculosis Risk Factors for British Herds Before and After the 2001 Foot-and-Mouth Epidemic: What have we Learned from the TB99 and CCS2005 Studies?A Bayesian integrative genomic model for pathway analysis of complex traitsA Bayesian approach to identify genes and gene-level SNP aggregates in a genetic analysis of cancer data.Objective Bayes model selection in probit models.
P2860
Q28393920-9018B513-ACBD-4257-BA80-4BF17AFCE337Q33530015-A9B834D2-3BDB-43E0-A72C-DD357CC7249FQ33583545-0A0321CB-BD60-4BD5-976F-6BC1E76A8EFEQ34085632-DB86B49F-B9C6-473D-A5A0-8B9DB65DD762Q34570894-6F36DE37-4DC5-4DB3-9977-8CB9897BCC6AQ34884883-74703247-C788-492B-9FB1-D41FE6EBC758Q35075846-D0C665D5-887A-4BEA-A2C6-846F67FD2D4AQ35118533-0C7E4EED-0B0C-43B1-8A3C-C8A372D5EA39Q35862611-F30473A7-3C76-4107-9167-9EDD8457A0EFQ37582383-9A025253-B526-4A41-84EF-9F930984CEDCQ37728214-0794D666-409B-4A54-AEE0-F2651C2F5269Q37734569-3FD5CC18-58F7-4246-9210-D4ACF85E6AF0Q38170572-7913C77F-7340-4B4D-8310-628F56E7AB63Q39372106-2EF5D903-F541-417C-8C67-B648C39674D5Q42063470-09C47B77-819E-48D7-971C-4C33E6DFD8FAQ51475799-71F8C151-35F2-41D5-B433-15169A0589F6
P2860
Finding factors influencing risk: comparing Bayesian stochastic search and standard variable selection methods applied to logistic regression models of cases and controls.
description
2008 nî lūn-bûn
@nan
2008年の論文
@ja
2008年論文
@yue
2008年論文
@zh-hant
2008年論文
@zh-hk
2008年論文
@zh-mo
2008年論文
@zh-tw
2008年论文
@wuu
2008年论文
@zh
2008年论文
@zh-cn
name
Finding factors influencing ri ...... models of cases and controls.
@en
type
label
Finding factors influencing ri ...... models of cases and controls.
@en
prefLabel
Finding factors influencing ri ...... models of cases and controls.
@en
P2860
P356
P1476
Finding factors influencing ri ...... n models of cases and controls
@en
P2093
Robert K Yu
Sanjay Shete
P2860
P304
P356
10.1002/SIM.3434
P407
P577
2008-12-01T00:00:00Z