2019
DOI: 10.1002/bimj.201800124
|View full text |Cite
|
Sign up to set email alerts
|

Assessment of local influence for the analysis of agreement

Abstract: The concordance correlation coefficient (CCC) and the probability of agreement (PA) are two frequently used measures for evaluating the degree of agreement between measurements generated by two different methods. In this paper, we consider the CCC and the PA using the bivariate normal distribution for modeling the observations obtained by two measurement methods. The main aim of this paper is to develop diagnostic tools for the detection of those observations that are influential on the maximum likelihood esti… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1

Citation Types

0
1
0

Year Published

2020
2020
2024
2024

Publication Types

Select...
5

Relationship

0
5

Authors

Journals

citations
Cited by 6 publications
(1 citation statement)
references
References 25 publications
0
1
0
Order By: Relevance
“…In the context of goodness of fit, Vonesh et al (1996) proposed a modified Lin's CCC for choosing models that have a better agreement between observed and the predicted values. Recently Stevens et al (2017) and Chodhary and Nagaraja (2017) developed the probability of agreement, and Leal et al (2019) studied the local influence of the CCC and the probability of agreement considering both first-and second-order measures under the case-weight perturbation scheme. Atkinson and Nevill (1997) critiqued the CCC because any correlation coefficient is highly dependent on the measurement range.…”
Section: Introductionmentioning
confidence: 99%
“…In the context of goodness of fit, Vonesh et al (1996) proposed a modified Lin's CCC for choosing models that have a better agreement between observed and the predicted values. Recently Stevens et al (2017) and Chodhary and Nagaraja (2017) developed the probability of agreement, and Leal et al (2019) studied the local influence of the CCC and the probability of agreement considering both first-and second-order measures under the case-weight perturbation scheme. Atkinson and Nevill (1997) critiqued the CCC because any correlation coefficient is highly dependent on the measurement range.…”
Section: Introductionmentioning
confidence: 99%