• Corpus ID: 207780048

Correcting for attenuation due to measurement error

@article{Moss2019CorrectingFA,
  title={Correcting for attenuation due to measurement error},
  author={Jonas Moss},
  journal={arXiv: Methodology},
  year={2019}
}
  • Jonas Moss
  • Published 9 July 2019
  • Geology
  • arXiv: Methodology
I present a frequentist method for quantifying uncertainty when correcting correlations for attenuation due to measurement error. The method is conservative but has far better coverage properties than the methods currently used when sample sizes are small. I recommend the use of confidence curves in favor of confidence intervals when this method is used. I introduce the R package "attenuation" which can be used to calculate and visualize the methods described in this paper. 
View PDF on arXiv
2 Citations
Methods Citations
1

Figures from this paper

2 Citations

Citation Type

Citation Type

Capturing the Environmental Impact of Individual Lifestyles: Evidence of the Criterion Validity of the General Ecological Behavior Scale
Do behavioral measures of ecological lifestyles reflect actual environmental impact? Three convenience samples of German adults (N = 881) completed such a measure, the General Ecological Behavior…
The 25-Item Ontario Child Health Study Emotional Behavioural Scales-Brief Version (OCHS-EBS-B): Test-Retest Reliability and Construct Validity When Used as Categorical Measures
TLDR
Although falling short of equivalence, the results suggest on balance that the reliability and validity of the two instruments for classifying child psychiatric disorder assessed by parents are highly comparable.

References

SHOWING 1-10 OF 20 REFERENCES
Correlation Attenuation Due to Measurement Error
TLDR
Results indicate that the bootstrap deattenuated correlation provided adequate percentile CI coverage in all but three conditions, and the bias-corrected and accelerated CI provided adequate coverage under all simulation conditions.
The correction for attenuation due to measurement error: clarifying concepts and creating confidence sets.
TLDR
Three different Monte-Carlo methods are presented, each offering a different way of examining confidence sets under the new conceptualization for CAME, and the author suggests that inference requires confidence sets that demarcate those population parameters likely to have produced an obtained value.
Two Approaches for Correcting Correlation Attenuation Caused by Measurement Error: Implications for Research Practice
This study focused on the issue of measurement reliability and its attenuation on correlation between two composites and two seemingly different approaches for correcting the attenuation. As…
Inferential procedures for correlation coefficients corrected for attenuation
A model and computational procedure based on classical test score theory are presented for determination of a correlation coefficient corrected for attenuation due to unreliability. Next,…
Confidence Curves: An Omnibus Technique for Estimation and Testing Statistical Hypotheses
Abstract A standard practice of physical scientists is to report estimates (“measurements”) accompanied by their standard errors (or alternatively “average errors” or “probable errors”). Such reports…
On the distribution of the maximum likelihood estimator of Cronbach's alpha
The asymptotic normal distribution of the maximum likelihood estimator of Cronbach's alpha (under normality) is derived for the case when no assumptions are made about the covariances among items.…
A Statistical Inference Course Based on p-Values
TLDR
An alternative approach to teaching this course is presented, built around p-values, emphasizing provably valid inference for all sample sizes.
Coefficient alpha and the reliability of composite measurements.
TLDR
It is pointed out that the statement that “coefficientα is equal to the mean of the split-half reliabilities” is true only under the restricted condition assumed by Cronbach in the body of his derivation of this result.
Testing Statistical Hypotheses
The General Decision Problem.- The Probability Background.- Uniformly Most Powerful Tests.- Unbiasedness: Theory and First Applications.- Unbiasedness: Applications to Normal Distributions.-…
The proof and measurement of association between two things.
  • C. Spearman
  • Education
    International journal of epidemiology
  • 2010
TLDR
The present article is a commencement at attempting to remedy this deficiency of scientific correlation, and the meaning and working of the various formulæ have been explained sufficiently, it is hoped, to render them readily usable even by those whose knowledge of mathematics is elementary.
...
1
2
...