Sample size calculation for an agreement study

Liao, Jason J. Z.

doi:10.1002/pst.382

Cited by 61 publications

(47 citation statements)

References 19 publications

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“…First, the relatively small sample size and its homogeneity could have an impact on the results. Recommendations about sample sizes for agreement studies are few [41] and vary widely, ranging from at least 32 participants [42] to over 100 participants [43]. This makes naturally difficult to draw any certain conclusion about optimal sample sizes.…”

Section: Discussionmentioning

confidence: 99%

Comparison between logbook-reported and objectively-assessed physical activity and sedentary time in breast cancer patients: an agreement study

Mazzoni

Nordin

Berntsen

et al. 2017

BMC Sports Sci Med Rehabil

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BackgroundIncreasing physical activity (PA) and decreasing sedentary time (ST) have important health effects among breast cancer patients, a growing population group. PA and sedentary behaviors are complex multi-dimensional behaviors and are challenging to monitor accurately. To date few studies have compared self-reports and objective measurement in assessing PA and ST in women undergoing breast cancer treatments. The aim of the present study was to compare self-reports and objective measures for assessing daily time spent in moderate-intensity physical activity (MPA), vigorous-intensity physical activity (VPA) and ST in women undergoing breast cancer treatments.MethodsBaseline data from 65 women with breast cancer scheduled to undergo adjuvant treatment was included. Daily time spent in MPA, VPA and ST was assessed by a study-specific logbook and the SenseWear Armband mini (SWA). The level of agreement between the two measurement methods was then determined by performing Bland-Altman plots with limits of agreements, and calculating Spearman’s rank correlation coefficients.ResultsThe mean difference between the logbook and SWA with limits of agreement was 14 (±102) minutes for MPA, 1 (±21) minute for VPA and −196 (±408) minutes for ST, respectively. The logbook reported an average of 34 and 50% higher values than the SWA for MPA and VPA, as well as an average of 27% lower values for ST (P < 0.05). The Spearman’s rank correlation coefficients showed that the differences between the methods increased as the average amount of time spent in PA and ST increased (P < 0.01).ConclusionsThe results imply that the two measurement methods have limited agreement and cannot be used interchangeably.

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Section: Discussionmentioning

confidence: 99%

Comparison between logbook-reported and objectively-assessed physical activity and sedentary time in breast cancer patients: an agreement study

Mazzoni

Nordin

Berntsen

et al. 2017

BMC Sports Sci Med Rehabil

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“…Sample size calculations were based on a ρ 0 (H0 lowest acceptable concordance correlation coefficient [CCC]) of 0.9 and a ρ 1 (H1 expected outcome of CCC) of 0.95, yielding a required sample size of n = 32 observations using a significance ( α ) = .05 and a power (1 − β ) of 0.80 14 . In our case, 40 observed scans from 20 patients were used.…”

Section: Methodsmentioning

confidence: 99%

Critical appraisal of multidimensional CT measurements following acute open repair of type A aortic dissection

et al. 2020

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Introduction To identify patients with aneurysmal degeneration of the native aorta following type A aortic dissection (TAAD), reproducible serial measurements of aortic dimensions are critical. We used a systematic workflow for measuring aortic geometry following TAAD, using computed tomography angiography data, and test its reproducibility. Methods The workflow for aortic measurements included centerline generation, luminal diameter, and area measurement at six anatomically defined locations along the aorta and luminal volumetric measurements in the descending aorta. Two independent observers measured the aortic geometry in 20 surgically repaired TAAD patients, preoperatively and at 3 months follow‐up. To test reproducibility, intraobserver and interobserver agreement scores were analyzed using a concordance correlation coefficient (CCC). Results The interobserver agreement scores of the diameter, area, and volumetric measurements in the descending aorta were acceptable. The agreement scores of the area measurements were highest, with CCCs ranging from 0.909 to 0.984. Luminal diameter measurements scored lower than luminal area measurements and were least reproducible at the mid aortic arch (CCC < 0.886). Overall, intraobserver agreement scores were better than interobserver agreement scores (SD of mean difference was 1.89 vs 1.94 for intraobserver vs interobserver diameter measurements, and 0.61 vs 0.66 for area measurements). Conclusion Although overall reproducibility was acceptable in descending aortic measurements, our results show that it remains challenging to reliably measure luminal diameters, compared with areas. To aid identification of early adverse remodeling following acute TAAD, novel two‐ and three‐dimensional measurement techniques are needed that capture locoregional changes in the false lumen and true lumen morphology more accurately.

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“…As demonstrated in Liao [16], the sample size is an increasing function of the tolerance probability β but a decreasing function of the discordance rate α. The discordance rate and tolerance probability play similar roles as the significant level and the power in a hypothesis testing setting from the Neyman-Pearson framework.…”

Section: Quantifying An Agreementmentioning

confidence: 95%

Quantifying an Agreement Study

Liao¹

2015

The International Journal of Biostatistics

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In medical and other related sciences, clinical or experimental measurements usually serve as a basis for diagnostic, prognostic, therapeutic, and performance evaluations. Examples can be assessing the reliability of multiple raters (or measurement methods), assessing the suitability for tumor evaluation of using a local laboratory or a central laboratory in a randomized clinical trial (RCT), validating surrogate endpoints in a study, determining that the important outcome measurements are interchangeable among the evaluators in an RCT. Any elegant study design cannot overcome the damage by unreliable measurement. Many methods have been developed to assess the agreement of two measurement methods. However, there is little attention to quantify how good the agreement of two measurement methods is. In this paper, similar to the type I error and the power in describing a hypothesis testing, we propose quantifying an agreement assessment using two rates: the discordance rate and the tolerance probability. This approach is demonstrated through examples.

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Sample size calculation for an agreement study

Cited by 61 publications

References 19 publications

Comparison between logbook-reported and objectively-assessed physical activity and sedentary time in breast cancer patients: an agreement study

Comparison between logbook-reported and objectively-assessed physical activity and sedentary time in breast cancer patients: an agreement study

Critical appraisal of multidimensional CT measurements following acute open repair of type A aortic dissection

Quantifying an Agreement Study

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