A new approach for interval estimation and hypothesis testing of a certain intraclass correlation coefficient: the generalized variable method.

We consider the problems of interval estimation and hypothesis testing for the intraclass correlation coefficient in an interrater reliability study when both raters and subjects are assumed to be randomly selected from populations of raters and subjects, respectively. We propose a novel approach for the confidence interval estimation and hypothesis testing using the concepts of generalized confidence interval (GCI) and generalized P-values. A simulation study is conducted to investigate the coverage probabilities of the GCI approach relative to the modified large sample (MLS) approach. Both methods tend to provide somewhat conservative coverage. Relative to the MLS approach, the GCI approach is closer to the correct (nominal) coverage for a two-sided interval, but farther to the correct coverage for a one-sided lower interval. Unlike the MLS approach, the GCI approach can also easily provide P-values. The fact that the GCI approach is suitable for confidence interval estimation and obtaining P-values makes the GCI approach a suitable candidate for making inference about interrater reliability.

Tian L ，Cappelleri JC 《STATISTICS IN MEDICINE》

A modified large-sample approach to approximate interval estimation for a particular intraclass correlation coefficient.

We consider the problem of constructing a confidence interval for the intraclass correlation coefficient in an interrater reliability study when both raters and subjects are random effects in a two-way random effects model. A simulation study is conducted to investigate and compare the interval coverage per cents of three methods of approximation: (i) Satterthwaite's two moments, the standard approach; (ii) modified three moments, a newer approach; and (iii) modified large sample, the newest approach for this particular problem. One-sided lower and two-sided bounds are examined. For the two-moment approach, coverage of confidence intervals can be understated for not only one-sided bounds but also two-sided bounds. Coverage of confidence intervals for the modified large-sample approach is either correct or conservative and provides narrower two-sided widths than the modified three-moment approach, which can understate coverage on one-sided and two-sided bounds for two or three raters. The competing methods are illustrated with data from a reliability study of four raters evaluating the number of decayed, missing, and filled surfaces in the permanent teeth of ten subjects. Overall, the modified large-sample approach provides the most satisfactory performance of the three methods.

Cappelleri JC ，Ting N 《STATISTICS IN MEDICINE》

Interval estimation and hypothesis testing of intraclass correlation coefficients: the generalized variable approach.

In this paper, we propose a novel approach using the concept of generalized variable (GV) for the confidence interval estimation of the difference of two intraclass correlation coefficients under unequal family sizes. This approach can also easily provide P-values for hypothesis testing. Simulation results show that the GV approach can provide confidence intervals with good coverage properties and perform hypothesis testing with satisfactory type-I error control. Furthermore, the confidence intervals and P-values by GV approach can be easily obtained by simulation. Therefore the GV approach is a suitable candidate for making inference concerning two intraclass correlation coefficients.

Tian L 《STATISTICS IN MEDICINE》

Confidence interval construction for a difference between two dependent intraclass correlation coefficients.

Inferences for the difference between two dependent intraclass correlation coefficients (ICCs) may arise in studies in which a sample of subjects are each assessed several times with a new device and a standard. The ICC estimates for the two devices may then be compared using a test of significance. However, a confidence interval for a difference between two ICCs is more informative since it combines point estimation and hypothesis testing into a single inference statement. We propose a procedure that uses confidence limits for a single ICC to recover variance estimates needed to set confidence limits for the difference. An advantage of this approach is that it provides a confidence interval that reflects the underlying sampling distribution. Simulation results show that this method performs very well in terms of overall coverage percentage and tail errors. Two data sets are used to illustrate this procedure.

Ramasundarahettige CF ，Donner A ，Zou GY 《STATISTICS IN MEDICINE》

Inferences on standardized mean difference: the generalized variable approach.

The standardized mean difference has been widely used as the most common index of effect magnitude in many applied fields. In this paper, we propose a novel approach using the concept of generalized variable for the confidence interval estimation and hypothesis testing of standardized mean difference. Furthermore, we extend this approach to compare standardized mean differences between two studies or between two strata. Simulation results demonstrate that the proposed approach can provide confidence intervals with excellent coverage properties and can perform hypothesis testing with satisfactory type-I error control.

Tian L 《STATISTICS IN MEDICINE》