<p>An uncertainty analysis is used to assess the accuracy of the projections made, giving the percentage at which it’s likely to achieve (or exceed) the projected (base) value. (Example: the costs of hospital admission period are likely to be higher than the projections in 37% of the cases.) The uncertainty analysis also gives the averages (certainty equal to 50%) and the confidence intervals (the most likely values ranging from 10% to 90% percentiles).</p><p>Results of the Uncertainty Analysis.</p
A model's purpose is to inform medical decisions and health care resource allocation. Modelers emplo...
Uncertainty assessment is a cornerstone in model-based health economic evaluations (HEEs) that infor...
Objectives: Decision makers adopt health technologies based on health economic models that are subje...
Come up with a probable bound on a measured value xtrue = xmeas ± ux at C % confidence or n:1 odds ...
BACKGROUND: A number of recent papers have proposed methods to calculate confidence intervals and p ...
<p>Experts’ assessment of the uncertainty of parameter estimates in their case study (numbers indica...
A measurement result is incomplete without a statement of its 'uncertainty' or 'margin of error'. Bu...
A model’s purpose is to inform medical decisions and health care resource allocation. Modelers emplo...
Risk prediction models are crucial for assessing the pretest probability of cancer and are applied t...
Uncertainty analysis is the process of identifying limitations in scientific knowledge and evaluatin...
A model's purpose is to inform medical decisions and health care resource allocation. Modelers emplo...
UNLABELLED: Accounting for uncertainty is now a standard part of decision-analytic modeling and is r...
I I It is no longer acceptable, in most circles, to present experimental results without describing ...
In recent years, considerable attention has been devoted to the development of statistical methods f...
In areas of risk assessment ranging from terrorism to health, safety, and the environment, authorita...
A model's purpose is to inform medical decisions and health care resource allocation. Modelers emplo...
Uncertainty assessment is a cornerstone in model-based health economic evaluations (HEEs) that infor...
Objectives: Decision makers adopt health technologies based on health economic models that are subje...
Come up with a probable bound on a measured value xtrue = xmeas ± ux at C % confidence or n:1 odds ...
BACKGROUND: A number of recent papers have proposed methods to calculate confidence intervals and p ...
<p>Experts’ assessment of the uncertainty of parameter estimates in their case study (numbers indica...
A measurement result is incomplete without a statement of its 'uncertainty' or 'margin of error'. Bu...
A model’s purpose is to inform medical decisions and health care resource allocation. Modelers emplo...
Risk prediction models are crucial for assessing the pretest probability of cancer and are applied t...
Uncertainty analysis is the process of identifying limitations in scientific knowledge and evaluatin...
A model's purpose is to inform medical decisions and health care resource allocation. Modelers emplo...
UNLABELLED: Accounting for uncertainty is now a standard part of decision-analytic modeling and is r...
I I It is no longer acceptable, in most circles, to present experimental results without describing ...
In recent years, considerable attention has been devoted to the development of statistical methods f...
In areas of risk assessment ranging from terrorism to health, safety, and the environment, authorita...
A model's purpose is to inform medical decisions and health care resource allocation. Modelers emplo...
Uncertainty assessment is a cornerstone in model-based health economic evaluations (HEEs) that infor...
Objectives: Decision makers adopt health technologies based on health economic models that are subje...