Corrected profile likelihood confidence interval for binomial paired incomplete data

Pradhan, Vivek; Menon, Sandeep; Das, Ujjwal

doi:10.1002/pst.1551

Cited by 2 publications

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References 28 publications

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“…The problem of testing the equality and constructing CI for the difference of two correlated proportions in the presence of incomplete paired binary data has received considerable attention in past years. For example, ones can refer to [ 2 – 6 ] for the large sample method, and [ 7 ] for the corrected profile likelihood method. When sample size is small, [ 8 ] proposed the exact unconditional test procedure for testing equality of two correlated proportions with incomplete correlated data.…”

Section: Introductionmentioning

confidence: 99%

Confidence intervals construction for difference of two means with incomplete correlated data

Tang

2016

BMC Med Res Methodol

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BackgroundIncomplete data often arise in various clinical trials such as crossover trials, equivalence trials, and pre and post-test comparative studies. Various methods have been developed to construct confidence interval (CI) of risk difference or risk ratio for incomplete paired binary data. But, there is little works done on incomplete continuous correlated data. To this end, this manuscript aims to develop several approaches to construct CI of the difference of two means for incomplete continuous correlated data.MethodsLarge sample method, hybrid method, simple Bootstrap-resampling method based on the maximum likelihood estimates (B1) and Ekbohm’s unbiased estimator (B2), and percentile Bootstrap-resampling method based on the maximum likelihood estimates (B3) and Ekbohm’s unbiased estimator (B4) are presented to construct CI of the difference of two means for incomplete continuous correlated data. Simulation studies are conducted to evaluate the performance of the proposed CIs in terms of empirical coverage probability, expected interval width, and mesial and distal non-coverage probabilities.ResultsEmpirical results show that the Bootstrap-resampling-based CIs B1, B2, B4 behave satisfactorily for small to moderate sample sizes in the sense that their coverage probabilities could be well controlled around the pre-specified nominal confidence level and the ratio of their mesial non-coverage probabilities to the non-coverage probabilities could be well controlled in the interval [0.4, 0.6].ConclusionsIf one would like a CI with the shortest interval width, the Bootstrap-resampling-based CIs B1 is the optimal choice.

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Section: Introductionmentioning

confidence: 99%

Confidence intervals construction for difference of two means with incomplete correlated data

Tang

2016

BMC Med Res Methodol

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Confidence interval construction for the difference between two correlated proportions with missing observations

Tang

et al. 2015

Journal of Biopharmaceutical Statistics

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Under the assumption of missing at random, eight confidence intervals (CIs) for the difference between two correlated proportions in the presence of incomplete paired binary data are constructed on the basis of the likelihood ratio statistic, the score statistic, the Wald-type statistic, the hybrid method incorporated with the Wilson score and Agresti-Coull (AC) intervals, and the Bootstrap-resampling method. Extensive simulation studies are conducted to evaluate the performance of the presented CIs in terms of coverage probability and expected interval width. Our empirical results evidence that the Wilson-score-based hybrid CI and the Wald-type CI together with the constrained maximum likelihood estimates perform well for small-to-moderate sample sizes in the sense that (i) their empirical coverage probabilities are quite close to the prespecified confidence level, (ii) their expected interval widths are shorter, and (iii) their ratios of the mesial non-coverage to non-coverage probabilities lie in interval [0.4, 0.6]. An example from a neurological study is used to illustrate the proposed methodologies.

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Corrected profile likelihood confidence interval for binomial paired incomplete data

Cited by 2 publications

References 28 publications

Confidence intervals construction for difference of two means with incomplete correlated data

Confidence intervals construction for difference of two means with incomplete correlated data

Confidence interval construction for the difference between two correlated proportions with missing observations

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