Showing papers on "Intraclass correlation published in 1978"

Approximate interval estimation for a certain intraclass correlation coefficient

Abstract: When the raters participating in a reliability study are a random sample from a larger population of raters, inferences about the intraclass correlation coefficient must be based on the three mean squares from the analysis of variance table summarizing the results: between subjects, between raters, and error. An approximate confidence interval for the parameter is presented as a function of these three mean squares.

Assessment of swimming performance of preschool children.

Abstract: The purpose of this research was to establish the validity and reliability of a swimming scale designed for children, ages 2 to 6 yr Subjects (N = 57) were tested on nine categories of tasks These tasks were selected from the skills traditionally included within the motor domain of swimming; therefore, the scale is assumed to be valid Intraclass correlation coefficients were used to estimate the interjudge objectivity, and within-day, and between-days reliabilities The range of values for each were: 99 to 98, 99 to 96, and 97 to 84, respectively As these values are acceptable, the swimming scale seems to be an appropriate instrument for assessing the performance of preschool children

Comment on Bartko's "On Various Intraclass Correlation Reliability Coefficients"

Abstract: The implications of generalizabil ity theory for the choice of an intraclass correlation coefficient as a measure of the generalizability of rating data are reviewed. The review suggests that the conclusions expressed in Bartko's article on the appropriateness of certain coefficients are not entirely warranted. Furthermore, citation of the classical .test theory literature shows that his conclusion about the Kuder-Richardson Formula 20 is not correct. Bartko (1976) compared four intraclass correlation coefficients that may be used as reliability coefficients for rating data and concluded that a one-way analysis of variance (ANOVA) intraclass correlation coefficient, discussed by Bartko (1966), provides the best formulation for the reliability of ratings. The conclusion was based on a demonstration that the advocated coefficient is the only one of the four that is large if and only if the within-subjects variance is small, a characteristic he claimed is desirable in a reliability coefficient. Bartko (1976) also reported the values of two intraclass correlation coefficients derived from a two-way ANOVA of dichotomous data originally reported by Winer (1971). The value of one coefficient, which was equal to the value obtained by applying the Kuder-Richardson Formula 20 (KR-20), was larger than the value of the coefficient reported by Bartko (1966). Based on this demonstration he concluded that if for some reason the computation of an intraclass correlation from a two-way ANOVA was desirable, the Bartko (1966) approach should be used. Further, he concluded that KR-20 produces "spuriously high intraclass correlations." (Bartko, 1976, p. 764.)

Possible biases in heritability estimates from intraclass correlation

Abstract: There is an inherent bias in intraclass correlations since the expectation of a ratio does not equal the ratio of expectations. A simple accurate approximation for this bias is derived, and it is found that the inherent bias is usually negligible. Selection of sires is known to bias half-sib heritability estimates, and appropriate formulae are given and discussed.

On the Utility of the E-Correlation Coefficient Concept in Psychological Research

Abstract: The term correlation coefficient has been defined in various ways. In this article the E-(correlation) coefficient concept is considered. Six characteristics of an E-coefficient are mentioned. For 23 similarity measures of interval, ordinal, dichotomous, and nominal data is considered whether they are E-coefficients or not. Finally, the importance of the concept is discussed.

Criterion-oriented grading system for preclinical operative dentistry laboratory course.

Abstract: The object of this study was to evaluate instructor reliabilities when using empirical or traditional and criterion-oriented grading methods. To do so, 52 sample preparations made in plastic teeth by freshman dental students in the preclinical operative dentistry laboratory course were graded by 12 instructors. The preparations included those for amalgam, inlay, and gold foil restorations. The instructors were divided into two groups according to their teaching experience. Intraclass correlation coefficients were calculated by using a one way analysis of variance technique. The criterion method, in general, yielded greater intraclass correlation coefficients. The increase in the intraclass correlation coefficient was found to be significant at the alpha = 0.10 error level for all restorations judged by experienced instructors. The different degrees of increase in correlation may be attributed to the vary ing clinical biases of the instructors and the differences in the types of preparations.

The number of families required for detecting the familial aggregation of a continuous attribute

Abstract: A formula is presented and graphs are displayed that provide the approximate power of a test for intraclass correlation. The results are useful for estimating the number of families required for detecting the familial aggregation of a continuous attribute.

On bartko's intraclass correlations of interrater reliability

Abstract: Summury.-Barcko's justification for rejecting Winer's "anchor point method" of intraclass correlation is reviewed. The issues of rater variance and the average intercorrelation were examined in terms of Winer's method and Bartko's two alternative formulations. There were three major conclusions: (1) Bartko's arguments regarding additive bias were statistically sound, however, they are virtually meaningless in the application of the intraclass correlation in an experimental or practical context; (2) Bartko's intradass correlation for the one-way model of analysis of variance is appropriate when it is desirable to include the rater variance term; (3) Winer's intraclass correlation for the two-way model of analysis of variance is appropriate when it is desirable to exclude rater variance. Bartko (1976, 1978) has recommendd two intraclass correlations for estimating the reliability of a single rating (Bartko, 1966) as substitutes for the "anchor point" approach presented by Winer (1971, pp. 289-296). Winer's intraclass correlation also happens to be the correlation most frequently cited in the psychometric literature (Ebel, 1951; Guilford, 1954; Maxwell & Pilliner, 1968; Wiggins, 1973). The three different correlations and their salient characteristics are displayed in Table 1. Bartko strongly advises against using ICC(2) primarily on the grounds that it is insensitive to additive bias. He indicates ". . . with Winer's approach, any adjustment of original rating data that leaves the raters' variance-covariance matrix unaltered will produce the same intraclass correlation coefficient, and thus numerous variations (of which additive bias is a subset) of the original data set can and will yield the same intraclass correlation" (p. 762). This paper examines the justification for that charge, the related issue of inclusion versus exclusion of rater variance, and the validity and utility of the two proposed alternative formulations. ADDITIVE BIAS Since the estimated ICC(2) from the variance of the means of persons is the ratio of the mean covariance among raters to the mean of the rater variances, any condition where the rater variances are equal, i.e., equal means, equal variances and unequal means, equal variances, reduces the intraclass correlation to the Pearson product-moment correlation. This is only possible when k = 2. Bartko's data sets la (identical ratings) and Ib (additive bias) illus

Some Sampling Characteristics of Three Estimators of the Intraclass Correlation

Abstract: Some sampling characteristics of three estimators of the intraclass correlation were investigated under a variety of conditions within the context of a one-way three treatment level random effects analysis of variance. The results promote caution in the use of all three estimators since they show both a large negative bias under most conditions and a large standard deviation. The three estimators differed very little in their degree of bias or in the magnitude of their standard errors.