Normalization of mean squared differences to measure agreement for continuous data

Almehrizi, Rashid S.

doi:10.1177/0962280213507506

Cited by 7 publications

(4 citation statements)

References 17 publications

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“… is the PDF of the xj scores given examinee a's ability. This PDF can be obtained through the Lord and Wingersky (1984) recursion formula using which was employed by Almehrizi (2013;2016).…”

Section: The New Section-level Person Fit Statisticmentioning

confidence: 99%

Residual-Based Person Fit Statistics over Test Sections

Almehrizi¹

2019

J. educ. psychol. stud.

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Most tests are composed of multiple sections (each section has group of items) such as different item formats, different content category, competencies, different difficulty levels, test dimensions, testlets, and interpretive exercise items. Students could show unexpected and unacceptable responses across these sections. Studying person fit over item level cannot detect aberrant response over test sections. The study proposes a residual-based person fit statistic over test sections with a dichotomous IRT model. The paper demonstrates the new section-level person fit statistic and investigates its distributional properties and power of detecting aberrance in person responses with comparison to Wright's between person fit statistic. The proposed section-level person fit statistic shows superior distributional properties with both true and real ability and item parameters. Moreover, the performance of the proposed person fit statistic is also examined with real data.

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Section: The New Section-level Person Fit Statisticmentioning

confidence: 99%

Residual-Based Person Fit Statistics over Test Sections

Almehrizi¹

2019

J. educ. psychol. stud.

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“…The best matching position is found in the reference frame (usually the adjacent frame of the target frame) for each block. There are many measures of matching degree, including SAD (Sum of Absolute Differences) [ 29 ], MSD (Mean Square Differences) [ 30 ] and NCC (Normalized Cross Correlation) [ 31 ]. The best matching location search methods include FS (Full Search) [ 32 ], TSS (Three-Step Search), NTSS (New Three-Step Search) [ 33 ], and 4SS (Four-Step Search) [ 34 ].…”

Section: Introductionmentioning

confidence: 99%

A Displacement Estimated Method for Real Time Tissue Ultrasound Elastography

Zhang

et al. 2021

Mobile Netw Appl

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As an important means of medical imaging, elastic imaging is an indispensable part of mobile telemedicine. Ultrasound elastography has become a research hotspot because it can accurately measure soft tissue lesions. Displacement estimation is the most important step in ultrasound elastography. At present, the phase zero search method is an accurate and fast displacement estimation method. However, when the displacement exceeds 1/4 wavelength, it is invalid. The accuracy of block matching method is not high, but it is suitable for large displacement, so it can overcome this shortcoming. It is worth noting that the quality-guided block matching method has good robustness under complex mutation conditions. It can provide prior knowledge to increase the robustness of the phase-zero search under large displacement conditions. So we propose a novel displacement estimation method for real time tissue ultrasound elastography, which combines the quality-guided block matching method and the phase-zero search method. The experimental results show that this method is more accurate, faster and robust than other displacement estimation methods.

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“…Examples of scaled scores include percentile ranks, age equivalents, standardized scores, and normalized scores. Reliability of the aforementioned scores was investigated abundantly in previous research studies (e.g., Almehrizi, 2013Almehrizi, , 2016Brennan & Lee, 1999;Feldt & Qualls, 1998;Kolen & Lee., 2011;Kolen et al, 1992;Kolen et al, 2012;Lee, 2007) which concluded that there is a need for investigating the reliability of all types of test scaled scores besides the reliability of summed scores. The Standards for Educational and Psychological Testing (American Educational Research Association, American Psychological Association, & National Council of Measurement in Education, 2014) emphasize that reliability should be examined for all scores that are employed in test reports for better interpretation and utilization of test scores.…”

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confidence: 99%

Reconceptualization of Coefficient Alpha Reliability for Test Summed and Scaled Scores

Almehrizi

2022

Educational Measurement

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Coefficient alpha reliability persists as the most common reliability coefficient reported in research. The assumptions for its use are, however, not well‐understood. The current paper challenges the commonly used expressions of coefficient alpha and argues that while these expressions are correct when estimating reliability for summed scores, they are not appropriate to extend coefficient alpha to correctly estimate the reliability for nonlinearly transformed scaled scores such as percentile ranks and stanines. The current paper reconceptualizes coefficient alpha as a complement of the ratio of two unbiased estimates of the summed score variance. These include conditional summed score variance assuming uncorrelated item scores (gives the error score variance) and unconditional summed score variance incorporating intercorrelated item scores (gives the observed score variance). Using this reconceptualization, a new equation of coefficient generalized alpha is introduced for scaled scores. Coefficient alpha is a special case of this new equation since the latter reduces to coefficinet alpha if the scaled scores are the summed scores themselves. Two applications (cognitive and psychological assessments) are used to compare the performance (estimation and bootstrap confidence interval) of the reliability coefficients for different scaled scores. Results support the new equation of coefficient generalized alpha and compare it to coefficient generalized beta for parallel test forms. Coefficient generalized alpha produced different reliability values, which were larger than coefficient generalized beta for different scaled scores.

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Normalization of mean squared differences to measure agreement for continuous data

Cited by 7 publications

References 17 publications

Residual-Based Person Fit Statistics over Test Sections

Residual-Based Person Fit Statistics over Test Sections

A Displacement Estimated Method for Real Time Tissue Ultrasound Elastography

Reconceptualization of Coefficient Alpha Reliability for Test Summed and Scaled Scores

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