China 
Africa 
Explore chapters and articles related to this topic
Digital joint ROM measurement tool for geriatric rehabilitation assessment
Published in Shin-ya Nishizaki, Masayuki Numao, Jaime Caro, Merlin Teodosia Suarez, Theory and Practice of Computation, 2019
C.Y. Ong, M.M. Paragas, B.C. Huang
An intra-rater reliability test was conducted to verify the consistency of the developed device between its successive repetitions for measurement by the same rater or examiner. An Intraclass Correlation Coefficient (ICC) statistical technique was used in this testing as it is used to measure the reliability of measurement or ratings. The ICC of the DigiROM tool for both elbow flexion and hip flexion are 0.716 and 0.550, respectively, which are interpreted in the ICC as a moderate reliability and acceptable measure in measuring the two exercises.
Cluster analysis and multi-level modeling for evaluating the impact of rain on aggressive lane-changing characteristics utilizing naturalistic driving data
Published in Journal of Transportation Safety & Security, 2022
Anik Das, Md Nasim Khan, Mohamed M. Ahmed, Shaun S. Wulff
Equations (8) and (9) can be combined to obtain where is the lane-changing duration for event and driver is the combined model intercept, is the fixed slope coefficient for explanatory variable is the driver level random intercept, is the lane-changing event level error term (Blissett, 2017; Goldstein, 2011). Equation 10 represents the random intercept model with fixed slope coefficients. It is assumed that the random terms and are statistically independent. An intraclass correlation coefficient (ICC) can be used to measure the degree of correlation among observations within a specific group (Deligianni, Quddus, Morris, Anvuur, & Reed, 2017). For a two-level random intercept model, ICC can be calculated using Equation 11. where is the intercept variance of the random intercept model at level 2 (i.e., driver level) and is the variance of the level 1 residuals (i.e., lane-changing event).
Partially-automated individualized assessment of higher education mathematics
Published in International Journal of Mathematical Education in Science and Technology, 2022
Each second-marking experiment had a piece of work which was marked by an original marker and at least one second-marker. To assist with interpretation, comments on differences in the marks and the intraclass correlation coefficient (ICC) are presented. The intraclass correlation coefficient (ICC) is used to assess measurement error in judgements made by humans. A two way model on single score data ICC which considers the agreement between raters is computed. This takes no account of any ‘true’ value of the mark, if such a thing exists, but only considers the level of agreement between multiple markers. This means the ICC rating given depends on the reliability of the markers. For this reason, only people who have professionally marked student work in universities will be used as markers, for a reasonable expectation of reliability.
Feel the image: The role of emotions in the image-seeking process
Published in Human–Computer Interaction, 2019
Lev Poretski, Joel Lanir, Ofer Arazy
We calculated the Intraclass Correlation coefficient (two-way mixed, single measures) to measure the level of agreement among the participants on their emotional valence assessment of the image-seeking tasks. Intraclass Correlation Coefficient (ICC) is commonly used in measurements of consistency and level of agreement between different independent raters on the same concept. The ICC coefficient is measured on a scale from 0 to 1 where ICC < 0.3 indicates poor agreement, 0.3–0.4 indicates fair agreement, 0.4–0.6 indicates moderate agreement, 0.7–0.8 indicates strong agreement, and ICC > 0.8 indicates almost perfect agreement (Shrout & Fleiss, 1979). Table 3 presents the results of the reliability analysis for both studies.