scholarly journals Improved confidence intervals for the sensitivity at a fixed level of specificity of a continuous-scale diagnostic test

2005 ◽  
Vol 24 (3) ◽  
pp. 465-477 ◽  
Author(s):  
Xiao-Hua Zhou ◽  
Gengsheng Qin
Keyword(s):  
Confidence Intervals ◽  
Diagnostic Test ◽  
Fixed Level ◽  
Continuous Scale

Inference for econometric modeling in antidumping, countervailing duty and safeguard investigations

2009 ◽  
Vol 8 (4) ◽  
pp. 545-557 ◽  
Author(s):  
JAMES J. FETZER
Keyword(s):  
Confidence Intervals ◽  
Econometric Models ◽  
Econometric Modeling ◽  
P Values ◽  
Flexible Approach ◽  
Fixed Level ◽  
Point Estimates ◽  
Level Of Confidence ◽  
Significance Levels

AbstractThis paper examines how to make inferences from econometric models prepared for antidumping, countervailing duty, and safeguard investigations. Analysis of these models has typically entailed drawing inferences from point estimates that are significantly different from zero at a fixed level of confidence. This paper suggests a more flexible approach of drawing inferences using confidence intervals at various significance levels and reporting p-values for the relevant test of injury. Use of confidence intervals and p-values to identify insights and data patterns would have more impact on USITC trade remedy determinations than definitive conclusions about injury based on whether estimates are statistically significant.

Exact confidence limits for prevalence of a disease with an imperfect diagnostic test

2010 ◽  
Vol 138 (11) ◽  
pp. 1674-1678 ◽  
Author(s):  
J. REICZIGEL ◽  
J. FÖLDI ◽  
L. ÓZSVÁRI
Keyword(s):  
Confidence Intervals ◽  
Diagnostic Test ◽  
Sensitivity And Specificity ◽  
Simulation Study ◽  
Confidence Level ◽  
Asymptotic Methods ◽  
Real Life ◽  
Disease Status ◽  
Confidence Limits ◽  
Extensive Simulation

SUMMARYEstimation of prevalence of disease, including construction of confidence intervals, is essential in surveys for screening as well as in monitoring disease status. In most analyses of survey data it is implicitly assumed that the diagnostic test has a sensitivity and specificity of 100%. However, this assumption is invalid in most cases. Furthermore, asymptotic methods using the normal distribution as an approximation of the true sampling distribution may not preserve the desired nominal confidence level. Here we proposed exact two-sided confidence intervals for the prevalence of disease, taking into account sensitivity and specificity of the diagnostic test. We illustrated the advantage of the methods with results of an extensive simulation study and real-life examples.

scholarly journals New confidence intervals for the difference between two sensitivities at a fixed level of specificity

2006 ◽  
Vol 25 (20) ◽  
pp. 3487-3502 ◽  
Author(s):  
Gengsheng Qin ◽  
Yu-Sheng Hsu ◽  
Xiao-Hua Zhou
Keyword(s):  
Confidence Intervals ◽  
Fixed Level ◽  
The Difference
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