Two Approaches for Correcting Correlation Attenuation Caused by Measurement Error: Implications for Research Practice

By Xitao Fan. 2003

98 citations recorded by the source corpus.

Subfields: Computer Networks and Communications, Management Science and Operations Research

View Paper: https://www.semanticscholar.org/paper/c9232e0caba15bb5ec4d12f402c885c1e9d2d986

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In Computer Networks and Communications

In Management Science and Operations Research

Citations in the corpus

Changing philosophies and tools for statistical inferences in behavioral ecology (2009, methodology): “For example, formulas exist to correct for the downward bias that low repeatability due to within-subject variation raises in the calculation of correlation coefficients and regression slopes ( Fan 2003; McArdle 2003; Adolph and Hardin 2007; see also Figure 5). If both dependent and independent var”
Meritocracy, Self-Concerns, and Whites' Denial of Racial Inequity (2012, background): “Latent variable modeling serves to disattenuate associations for unreliability (Fan, 2003) and, moreover, the anti-Black discrimination and White privilege measures exhibited”
Incremental effects of reward on experienced performance pressure: positive outcomes for intrinsic interest and creativity (2009, methodology): “The effects of attenuation caused by measurement error on calculated reliability becomes greater as the number of scale items decreases ( Fan, 2003 ), and only two items were used to assess performance pressure in the first two studies.”
At what sample size do latent variable correlations stabilize? (2018, background): “…disattenuation formula and measurement-error-free correlations estimated within a latent variable framework will be equal, to the extent that the assumption of essential tau-equivalence (i.e., equal factor loadings across all observed indicators of a latent variable) is satisfied (Fan, 2003).”
A Comparison of Latent Growth Models for Constructs Measured by Multiple Items (2007, background): “A sample size between 100 and 200 is the minimum recommended by Hamilton, Gagne, and Hancock (2003) and Fan (2003) for parameter estimation with univariate LGM. Data sets were simulated with either essentially congeneric or essentially tau-equivalent items.”