Integrating Metagenomic and Bayesian Analyses to Evaluate the Performance and Confidence of CrAssphage as an Indicator for Tracking Human Sewage Contamination in China

2021 ◽  
Author(s):  
Haiyang Chen ◽  
Chang Liu ◽  
Yuezhao Li ◽  
Yanguo Teng
Keyword(s):  
Bayesian Analyses ◽  
Sewage Contamination

Bayesian analyses of cognitive architecture.

2017 ◽  
Vol 22 (2) ◽  
pp. 288-303 ◽  
Author(s):  
Joseph W. Houpt ◽  
Andrew Heathcote ◽  
Ami Eidels
Keyword(s):  
Cognitive Architecture ◽  
Bayesian Analyses

Data and source code for "Bayesian analyses of seventeen winters of water vapor fluxes show bark beetles reduce sublimation"

2018 ◽  
Author(s):  
John M. Frank ◽  
William J. Massman ◽  
Brent E. Ewers ◽  
David G. Williams
Keyword(s):  
Water Vapor ◽  
Bark Beetles ◽  
Source Code ◽  
Bayesian Analyses

No Evidence that Experiencing Physical Warmth Promotes Interpersonal Warmth: Two Failures to Replicate Williams and Bargh (2008)

2018 ◽  
Author(s):  
Christopher Chabris ◽  
Patrick Ryan Heck ◽  
Jaclyn Mandart ◽  
Daniel Jacob Benjamin ◽  
Daniel J. Simons
Keyword(s):  
Null Hypothesis ◽  
Small Sample ◽  
Sample Sizes ◽  
Double Blind ◽  
Bayesian Analyses ◽  
Physical Warmth ◽  
Small Sample Sizes ◽  
Interpersonal Warmth

Williams and Bargh (2008) reported that holding a hot cup of coffee caused participants to judge a person’s personality as warmer, and that holding a therapeutic heat pad caused participants to choose rewards for other people rather than for themselves. These experiments featured large effects (r = .28 and .31), small sample sizes (41 and 53 participants), and barely statistically significant results. We attempted to replicate both experiments in field settings with more than triple the sample sizes (128 and 177) and double-blind procedures, but found near-zero effects (r = –.03 and .02). In both cases, Bayesian analyses suggest there is substantially more evidence for the null hypothesis of no effect than for the original physical warmth priming hypothesis.

Measuring human sewage contamination in surface waters using human and bacterial DNA markers

2018 ◽  
Vol 2018 (9) ◽  
pp. 4366-4391 ◽  
Author(s):  
A B M Tanvir Pasha ◽  
Adrianne Lopez ◽  
Duc Phan ◽  
Jessica Hinojosa ◽  
Nikolas Carwile ◽  
...  
Keyword(s):  
Surface Waters ◽  
Dna Markers ◽  
Bacterial Dna ◽  
Sewage Contamination

SEWAGE CONTAMINATION OF BATHING BEACHES

1960 ◽  
Vol 1 (21) ◽  
pp. 818-819
Keyword(s):  
Sewage Contamination

CAN BAYESIAN METHODS MAKE DATA AND ANALYSES MORE RELEVANT TO DECISION MAKERS?

2001 ◽  
Vol 17 (1) ◽  
pp. 114-122 ◽  
Author(s):  
Steven H. Sheingold
Keyword(s):  
Decision Making ◽  
Bayesian Methods ◽  
Paradigm Shift ◽  
Relevant Information ◽  
Decision Makers ◽  
Evidence Based ◽  
Critical Importance ◽  
Bayesian Approaches ◽  
Bayesian Analyses ◽  
And Performance

Decision making in health care has become increasingly reliant on information technology, evidence-based processes, and performance measurement. It is therefore a time at which it is of critical importance to make data and analyses more relevant to decision makers. Those who support Bayesian approaches contend that their analyses provide more relevant information for decision making than do classical or “frequentist” methods, and that a paradigm shift to the former is long overdue. While formal Bayesian analyses may eventually play an important role in decision making, there are several obstacles to overcome if these methods are to gain acceptance in an environment dominated by frequentist approaches. Supporters of Bayesian statistics must find more accommodating approaches to making their case, especially in finding ways to make these methods more transparent and accessible. Moreover, they must better understand the decision-making environment they hope to influence. This paper discusses these issues and provides some suggestions for overcoming some of these barriers to greater acceptance.

scholarly journals Posterior Belief Assessment: Extracting Meaningful Subjective Judgements from Bayesian Analyses with Complex Statistical Models

2015 ◽  
Vol 10 (4) ◽  
pp. 877-908 ◽  
Author(s):  
Daniel Williamson ◽  
Michael Goldstein
Keyword(s):  
Statistical Models ◽  
Bayesian Analyses ◽  
Posterior Belief

DR. LETHEBY ON WATER ANALYSIS AND SEWAGE CONTAMINATION.

The Lancet ◽  
1869 ◽  
Vol 93 (2384) ◽  
pp. 654-655
Keyword(s):  
Water Analysis ◽  
Sewage Contamination
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