A goodness-of-fit approach to inference procedures for the kappa statistic: Confidence interval construction, significance-testing and sample size estimation

1992 ◽  
Vol 11 (11) ◽  
pp. 1511-1519 ◽  
Author(s):  
Allan Donner ◽  
Michael Eliasziw
Keyword(s):  
Confidence Interval ◽  
Sample Size ◽  
Goodness Of Fit ◽  
Kappa Statistic ◽  
Significance Testing ◽  
Sample Size Estimation ◽  
Size Estimation

scholarly journals Sample Size for Assessing Agreement between Two Methods of Measurement by Bland−Altman Method

2016 ◽  
Vol 12 (2) ◽  
Author(s):  
Meng-Jie Lu ◽  
Wei-Hua Zhong ◽  
Yu-Xiu Liu ◽  
Hua-Zhang Miao ◽  
Yong-Chang Li ◽  
...  
Keyword(s):  
Confidence Interval ◽  
Sample Size ◽  
Statistical Inference ◽  
New Method ◽  
Sample Size Estimation ◽  
Size Estimation ◽  
Limits Of Agreement ◽  
Bland Altman Method ◽  
Agreement Assessment ◽  
Methods Of Measurement

Abstract:The Bland–Altman method has been widely used for assessing agreement between two methods of measurement. However, it remains unsolved about sample size estimation. We propose a new method of sample size estimation for Bland–Altman agreement assessment. According to the Bland–Altman method, the conclusion on agreement is made based on the width of the confidence interval for LOAs (limits of agreement) in comparison to predefined clinical agreement limit. Under the theory of statistical inference, the formulae of sample size estimation are derived, which depended on the pre-determined level of

scholarly journals A systematic review of the quality of conduct and reporting of survival analyses of tuberculosis outcomes in Africa

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Moses M. Ngari ◽  
Susanne Schmitz ◽  
Christopher Maronga ◽  
Lazarus K. Mramba ◽  
Michel Vaillant
Keyword(s):  
Systematic Review ◽  
Sample Size ◽  
Survival Function ◽  
Sample Size Estimation ◽  
Size Estimation ◽  
Survival Curves ◽  
Survival Analyses ◽  
Survival Regression

Abstract Background Survival analyses methods (SAMs) are central to analysing time-to-event outcomes. Appropriate application and reporting of such methods are important to ensure correct interpretation of the data. In this study, we systematically review the application and reporting of SAMs in studies of tuberculosis (TB) patients in Africa. It is the first review to assess the application and reporting of SAMs in this context. Methods Systematic review of studies involving TB patients from Africa published between January 2010 and April 2020 in English language. Studies were eligible if they reported use of SAMs. Application and reporting of SAMs were evaluated based on seven author-defined criteria. Results Seventy-six studies were included with patient numbers ranging from 56 to 182,890. Forty-three (57%) studies involved a statistician/epidemiologist. The number of published papers per year applying SAMs increased from two in 2010 to 18 in 2019 (P = 0.004). Sample size estimation was not reported by 67 (88%) studies. A total of 22 (29%) studies did not report summary follow-up time. The survival function was commonly presented using Kaplan-Meier survival curves (n = 51, (67%) studies) and group comparisons were performed using log-rank tests (n = 44, (58%) studies). Sixty seven (91%), 3 (4.1%) and 4 (5.4%) studies reported Cox proportional hazard, competing risk and parametric survival regression models, respectively. A total of 37 (49%) studies had hierarchical clustering, of which 28 (76%) did not adjust for the clustering in the analysis. Reporting was adequate among 4.0, 1.3 and 6.6% studies for sample size estimation, plotting of survival curves and test of survival regression underlying assumptions, respectively. Forty-five (59%), 52 (68%) and 73 (96%) studies adequately reported comparison of survival curves, follow-up time and measures of effect, respectively. Conclusion The quality of reporting survival analyses remains inadequate despite its increasing application. Because similar reporting deficiencies may be common in other diseases in low- and middle-income countries, reporting guidelines, additional training, and more capacity building are needed along with more vigilance by reviewers and journal editors.

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