Assessing Observer Bias in Observational Health Outcome Studies: Clinician and Patient Measures of Benefit and Bayesian Hierarchical Methods

2006 ◽  
Author(s):  
Mark Ratcliffe ◽  
Josep Maria Haro ◽  
Stathis Kontodimas ◽  
Miguel Angel Negrin ◽  
David Suarez ◽  
...  
Keyword(s):  
Health Outcome ◽  
Outcome Studies ◽  
Observer Bias ◽  
Bayesian Hierarchical ◽  
Bayesian Hierarchical Methods

The Use of Bayesian Hierarchical Methods to Assess Selection and Observer Bias in Observational Health Outcome Studies

2006 ◽  
Author(s):  
Mark Ratcliffe ◽  
Josep Maria Haro ◽  
Stathis Kontodimas ◽  
Miguel Angel Negrin ◽  
David Suarez ◽  
...  
Keyword(s):  
Health Outcome ◽  
Outcome Studies ◽  
Observer Bias ◽  
Bayesian Hierarchical ◽  
Bayesian Hierarchical Methods

scholarly journals Bayesian hierarchical methods for modeling electrical grid component failures

2020 ◽  
Vol 189 ◽  
pp. 106789
Author(s):  
Laurel N. Dunn ◽  
Ioanna Kavvada ◽  
Mathilde D. Badoual ◽  
Scott J. Moura
Keyword(s):  
Bayesian Hierarchical ◽  
Electrical Grid ◽  
Bayesian Hierarchical Methods ◽  
Component Failures

scholarly journals Trend Of Pharmacoeconomics And Health Outcome Studies In Turkey

2016 ◽  
Vol 19 (7) ◽  
pp. A482
Author(s):  
G Kockaya ◽  
FB Yenilmez ◽  
E Tuna
Keyword(s):  
Health Outcome ◽  
Outcome Studies

scholarly journals PHP141 Effects of Changing Health Policy on Pharmacoeconomics and Health Outcome Studies in Turkey

2012 ◽  
Vol 15 (7) ◽  
pp. A313-A314
Author(s):  
G. Kockaya ◽  
P. Daylan Kockaya ◽  
G. Ergin Oguzhan
Keyword(s):  
Health Outcome ◽  
Health Policy ◽  
Outcome Studies

scholarly journals Statistical Modeling in Nonlinear Systems

2005 ◽  
Vol 18 (16) ◽  
pp. 3388-3399 ◽  
Author(s):  
Edward P. Campbell
Keyword(s):  
Nonlinear Dynamics ◽  
Statistical Models ◽  
Lorenz System ◽  
Prediction Models ◽  
Climate Data ◽  
Bayesian Hierarchical ◽  
Alternative Approaches ◽  
The Lorenz System ◽  
Bayesian Hierarchical Methods ◽  
The Impact

Abstract The use of linear statistical methods in building climate prediction models is examined, particularly the use of anomalies. The author’s perspective is that the climate system is a nonlinear interacting system, so the impact of modeling using anomalies rather than observed data directly is considered. With reference to the Lorenz system and a simple model for regime dependence, it is shown that anomalies impair our ability to reconstruct nonlinear dynamics. Some alternative approaches in the literature that offer an attractive way forward are explored, focusing on Bayesian hierarchical methods to construct so-called physical–statistical models. The author’s view is that anomalies should be reserved in most cases as a tool for enhancing graphical representations of climate data. The exceptions are when the implicit assumptions underlying the use of anomalies are met or when an anomaly representation is physically motivated.

The Benefit through Spirituality/Religiosity Scale—A 6-Item Measure for Use in Health Outcome Studies

2008 ◽  
Vol 38 (4) ◽  
pp. 493-506 ◽  
Author(s):  
Arndt Büssing ◽  
Harold G. Koenig
Keyword(s):  
Health Outcome ◽  
Reliability And Validity ◽  
Epidemiological Studies ◽  
Outcome Studies ◽  
Internal Reliability ◽  
Beneficial Effects ◽  
Medical Centers ◽  
Religious Dimensions ◽  
Chronic Pain Conditions

Objective: We intended to develop a brief and compact scale which measures the beneficial effects of spirituality/religiosity (SpR) on several dimensions of patients' life concerns, to be used in health outcome studies. Method: To attain a short measure valid for spiritual and religious dimensions, we designed a scale based on tested items of an independent item pool of the already established SpREUK inventory, which measures SpR attitudes and convictions and holds an independent data pool addressing the support of life concerns through SpR. To validate the intended BENEFIT scale, reliability and factor analyses were performed utilizing 371 individuals with different chronic diseases recruited in various medical centers in Germany (exploratory analysis), while for the confirmatory analyses we used an independent pool of 229 patients with chronic pain conditions. Results: Six items addressed the beneficial effects of SpR of the patients' concerns, and thus were chosen for the BENEFIT scale. These items had a good internal reliability (Cronbach's alpha = 0.922). Primary factor analysis pointed to a 1-factor solution, which explained 72% of variance. Correlation analyses revealed that the BENEFIT scale correlated with both uniquely religious and spiritual attitudes. Conclusions: The data demonstrate the reliability and validity of the 6-item BENEFIT scale that captures a unique aspect of SpR that can be used in epidemiological studies and clinical trials for those who wish to assess both the external and internal dimensions of SpR. This brief instrument can be easily incorporated into almost any study of mental health, physical health, or quality of life.

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