Results 151 to 160 of about 1,818,807 (197)

Differences in dynamic motor selection in stuttering

Echeverria-Altuna I, Demirel B, Boettcher SE, Watkins KE, Nobre AC.   +4 more
europepmc   +1 more source

A Novel Method for Inserting Dose Levels Mid-Trial in Early-Phase Oncology Combination Studies. [PDF]

Stat Med
George M, Wadsworth I, Mozgunov P.
europepmc   +1 more source

Comparison of low vs high tidal volumes in one-lung ventilation during thoracic surgery: a propensity-weighted cohort study. [PDF]

Sci Rep
Braïk R, Berna P, Walbecq J, Germain Y, Flet T, Abou-Arab O.   +5 more
europepmc   +1 more source

Associations of metal mixtures in early pregnancy with lung function and asthma in mid-childhood in Project Viva. [PDF]

Am J Epidemiol
Thilakaratne R, Lin PD, Rifas-Shiman SL, Wright RO, Bradshaw PT, Balmes JR, Gold DR, Hubbard A, Oken E, Cardenas A.   +9 more
europepmc   +1 more source

Use of rescue noninvasive ventilation for post-extubation respiratory failure. [PDF]

Crit Care
Grieco DL, Jaber S, Zakynthinos S, Demoule A, Ricard JD, Navalesi P, Vaschetto R, Hraiech S, Klouche K, Frat JP, Lemiale V, Fanelli V, Chanques G, Longhini F, Mancebo J, Gualano MR, Ferreyro BL, Brochard LJ, Antonelli M, Maggiore SM, RINO trial study group.   +20 more
europepmc   +1 more source

Contributions of Attention to Learning in Multidimensional Reward Environments. [PDF]

J Neurosci
Wang MC, Soltani A.
europepmc   +1 more source

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Constrained Noninformative Priors in Risk Assessment

Reliability Engineering and System Safety, 1996
Abstract A constrained noninformative prior distribution, a generalization of the Jeffreys noninformative prior, is defined for a single unknown parameter as the distribution corresponding to the maximum entropy distribution, subject to the assumed constraint(s), in the transformed model where the unknown parameter is approximately a location ...
Corwin L Atwood
exaly   +2 more sources

Bayesian Estimation of the Number of Species Using Noninformative Priors

Biometrical Journal, 2008
AbstractConsider a sample of animal abundances collected from one sampling occasion. Our focus is in estimating the number of species in a closed population. In order to conduct a noninformative Bayesian inference when modeling this data, we derive Jeffreys and reference priors from the full likelihood.
John Bunge
exaly   +3 more sources