USING ADJUSTED WALD CONFIDENCE INTERVAL FOR A BINOMIAL PROPORTION

2020 ◽  
Vol 17 (2) ◽  
pp. 415-422
Author(s):  
Félix Almendra-Arao
Keyword(s):  
Confidence Interval ◽  
Binomial Proportion

scholarly journals Modified Clopper-Pearson Confidence Interval for Binomial Proportion

2014 ◽  
Vol 13 (4) ◽  
pp. 296 ◽  
Author(s):  
Desale Habtzghi ◽  
Chand K. Midha ◽  
Ashish Das
Keyword(s):  
Confidence Interval ◽  
Binomial Proportion

Interval estimation for a proportion using a double-sampling scheme with two fallible classifiers

2016 ◽  
Vol 27 (8) ◽  
pp. 2478-2503 ◽  
Author(s):  
Shi-Fang Qiu ◽  
Heng Lian ◽  
GY Zou ◽  
Xiao-Song Zeng
Keyword(s):  
Confidence Interval ◽  
Interval Estimation ◽  
Wald Test ◽  
Nuisance Parameters ◽  
Double Sampling ◽  
Bootstrap Confidence Interval ◽  
Sampling Schemes ◽  
Binomial Proportion ◽  
Credible Intervals ◽  
Percentile Bootstrap

Double-sampling schemes using one classifier assessing the whole sample and another classifier assessing a subset of the sample have been introduced for reducing classification errors when an infallible or gold standard classifier is unavailable or impractical. Inference procedures have previously been proposed for situations where an infallible classifier is available for validating a subset of the sample that has already been classified by a fallible classifier. Here, we consider the case where both classifiers are fallible, proposing and evaluating several confidence interval procedures for a proportion under two models, distinguished by the assumption regarding ascertainment of two classifiers. Simulation results suggest that the modified Wald-based confidence interval, Score-based confidence interval, two Bayesian credible intervals, and the percentile Bootstrap confidence interval performed reasonably well even for small binomial proportions and small validated sample under the model with the conditional independent assumption, and the confidence interval derived from the Wald test with nuisance parameters appropriately evaluated, likelihood ratio-based confidence interval, Score-based confidence interval, and the percentile Bootstrap confidence interval performed satisfactory in terms of coverage under the model without the conditional independent assumption. Moreover, confidence intervals based on log- and logit-transformations also performed well when the binomial proportion and the ratio of the validated sample are not very small under two models. Two examples were used to illustrate the procedures.

scholarly journals Improving interval estimation of binomial proportions

2008 ◽  
Vol 366 (1874) ◽  
pp. 2405-2418 ◽  
Author(s):  
X.H Zhou ◽  
C.M Li ◽  
Z Yang
Keyword(s):  
Confidence Interval ◽  
Edgeworth Expansion ◽  
Interval Estimation ◽  
Finite Sample ◽  
Theoretical Justification ◽  
Logit Transformation ◽  
Binomial Proportion ◽  
Coverage Probabilities ◽  
Sample Proportion ◽  
Jeffreys Interval

In this paper, we propose one new confidence interval for the binomial proportion; our interval is based on the Edgeworth expansion of a logit transformation of the sample proportion. We provide theoretical justification for the proposed interval and also compare the finite-sample performance of the proposed interval with the three best existing intervals—the Wilson interval, the Agresti–Coull interval and the Jeffreys interval—in terms of their coverage probabilities and expected lengths. We illustrate the proposed method in two real clinical studies.

Development of apical pits in chloride cells of the gills of Pimephales promelas after chronic exposure to acid water

1983 ◽  
Vol 41 ◽  
pp. 462-463
Author(s):  
Richard L. Leino ◽  
Jon G. Anderson ◽  
J. Howard McCormick
Keyword(s):  
Confidence Interval ◽  
Chronic Exposure ◽  
Lake Superior ◽  
Pimephales Promelas ◽  
Chloride Cells ◽  
Fathead Minnows ◽  
Secondary Lamellae ◽  
Untreated Water ◽  
Water Ph ◽  
Flow Through

Groups of 12 fathead minnows were exposed for 129 days to Lake Superior water acidified (pH 5.0, 5.5, 6.0 or 6.5) with reagent grade H2SO4 by means of a multichannel toxicant system for flow-through bioassays. Untreated water (pH 7.5) had the following properties: hardness 45.3 ± 0.3 (95% confidence interval) mg/1 as CaCO3; alkalinity 42.6 ± 0.2 mg/1; Cl- 0.03 meq/1; Na+ 0.05 meq/1; K+ 0.01 meq/1; Ca2+ 0.68 meq/1; Mg2+ 0.26 meq/1; dissolved O2 5.8 ± 0.3 mg/1; free CO2 3.2 ± 0.4 mg/1; T= 24.3 ± 0.1°C. The 1st, 2nd and 3rd gills were subsequently processed for LM (methacrylate), TEM and SEM respectively.Three changes involving chloride cells were correlated with increasing acidity: 1) the appearance of apical pits (figs. 2,5 as compared to figs. 1, 3,4) in chloride cells (about 22% of the chloride cells had pits at pH 5.0); 2) increases in their numbers and 3) increases in the % of these cells in the epithelium of the secondary lamellae.

Efficacy of Vitamin D on Chronic Heart Failure Among Adults

2020 ◽  
Vol 90 (1-2) ◽  
pp. 49-58 ◽  
Author(s):  
Wang Chunbin ◽  
Wang Han ◽  
Cai Lin
Keyword(s):  
Heart Failure ◽  
Vitamin D ◽  
Chronic Heart Failure ◽  
Left Ventricular Ejection Fraction ◽  
Confidence Interval ◽  
Left Ventricular ◽  
Left Ventricular Ejection ◽  
Controlled Trials ◽  
Ventricular Ejection Fraction ◽  
Randomized Controlled

Abstract. Vitamin D deficiency commonly occurs in chronic heart failure. Whether additional vitamin D supplementation can be beneficial to adults with chronic heart failure remains unclear. We conducted a meta-analysis to derive a more precise estimation. PubMed, Embase, and Cochrane databases were searched on September 8, 2016. Seven randomized controlled trials that investigated the effects of vitamin D on cardiovascular outcomes in adults with chronic heart failure, and comprised 592 patients, were included in the analysis. Compared to placebo, vitamin D, at doses ranging from 2,000 IU/day to 50,000 IU/week, could not improve left ventricular ejection fraction (Weighted mean difference, WMD = 3.31, 95% confidence interval, CL = −0.93 to 7.55, P < 0.001, I2 = 92.1%); it also exerts no beneficial effects on the 6 minute walk distance (WMD = 18.84, 95% CL = −24.85 to 62.52, P = 0.276, I2 = 22.4%) and natriuretic peptide (Standardized mean difference, SMD = −0.39, 95% confidence interval CL = −0.48 to 0.69, P < 0.001, I2 = 92.4%). However, a dose-response analysis from two studies demonstrated an improved left ventricular ejection fraction with vitamin D at a dose of 4,000 IU/day (WMD = 6.58, 95% confidence interval CL = −4.04 to 9.13, P = 0.134, I2 = 55.4%). The results showed that high dose vitamin D treatment could potentially benefit adults with chronic heart failure, but more randomized controlled trials are required to confirm this result.

Confidence Interval Pictures Can Give Better Inference Than Significance Testing

2006 ◽  
Author(s):  
Geoff Cumming ◽  
Melissa Coulson ◽  
Michelle Healey ◽  
Fiona Fidler
Keyword(s):  
Confidence Interval ◽  
Significance Testing

Using Connectionist Modules for Decision Support

1990 ◽  
Vol 29 (03) ◽  
pp. 167-181 ◽  
Author(s):  
G. Hripcsak
Keyword(s):  
Decision Support ◽  
Standard Deviation ◽  
Confidence Interval ◽  
Posterior Probability ◽  
Back Propagation ◽  
Connectionist Model ◽  
Test Set ◽  
The Third ◽  
Independent Test ◽  
Better Than

AbstractA connectionist model for decision support was constructed out of several back-propagation modules. Manifestations serve as input to the model; they may be real-valued, and the confidence in their measurement may be specified. The model produces as its output the posterior probability of disease. The model was trained on 1,000 cases taken from a simulated underlying population with three conditionally independent manifestations. The first manifestation had a linear relationship between value and posterior probability of disease, the second had a stepped relationship, and the third was normally distributed. An independent test set of 30,000 cases showed that the model was better able to estimate the posterior probability of disease (the standard deviation of residuals was 0.046, with a 95% confidence interval of 0.046-0.047) than a model constructed using logistic regression (with a standard deviation of residuals of 0.062, with a 95% confidence interval of 0.062-0.063). The model fitted the normal and stepped manifestations better than the linear one. It accommodated intermediate levels of confidence well.

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