scholarly journals Measurement Error and Earnings Dynamics: Some Estimates from the PSID Validation Study

1995 ◽  
Vol 13 (3) ◽  
pp. 305 ◽  
Author(s):  
Jörn-Steffen Pischke ◽  
Jorn-Steffen Pischke
Keyword(s):  
Measurement Error ◽  
Validation Study ◽  
Earnings Dynamics

scholarly journals Measurement error correction and sensitivity analysis in longitudinal dietary intervention studies using an external validation study

Biometrics ◽  
2019 ◽  
Vol 75 (3) ◽  
pp. 927-937 ◽  
Author(s):  
Juned Siddique ◽  
Michael J. Daniels ◽  
Raymond J. Carroll ◽  
Trivellore E. Raghunathan ◽  
Elizabeth A. Stuart ◽  
...  
Keyword(s):  
Sensitivity Analysis ◽  
Measurement Error ◽  
Error Correction ◽  
Validation Study ◽  
Intervention Studies ◽  
Dietary Intervention ◽  
External Validation ◽  
External Validation Study ◽  
Measurement Error Correction

Identifying reliable change in tactile temporal thresholds in multiple sclerosis: test-retest reliability

2006 ◽  
Vol 12 (5) ◽  
pp. 573-577 ◽  
Author(s):  
L N Brown ◽  
L M Metz ◽  
M Eliasziw
Keyword(s):  
Multiple Sclerosis ◽  
Measurement Error ◽  
Corpus Callosum ◽  
Validation Study ◽  
Outcome Measure ◽  
Retest Reliability ◽  
Real Change ◽  
Test Retest Reliability ◽  
Standard Error Of Measurement ◽  
Error Of Measurement

Background Tactile temporal thresholds are typically significantly higher (ie, prolonged) in multiple sclerosis (MS) patients when compared to controls and increase significantly during relapses, probably reflecting integrity of conduction across a portion of the corpus callosum. As part of an ongoing validation study of tactile temporal thresholds, the test-retest reliability of these thresholds was examined in patients with MS. Methods Tactile temporal thresholds were measured in 61 MS patients during two separate test sessions within three weeks. Test-retest reliability and the standard error of measurement were calculated. The threshold of change in tactile temporal thresholds in MS patients that would correspond to real change beyond measurement error with 95% certainty was also calculated. Results The test-retest reliability of this measure of tactile temporal thresholds was 0.93. The threshold indicating change beyond chance or measurement error with 95% certainty was 19 ms. Conclusions This measure of tactile temporal thresholds has excellent test - retest reliability and a change of greater than 19 ms is highly likely to represent real change. This measure is promising as a precise, reliable outcome measure in MS.

scholarly journals A Method to adjust for measurement error in multiple exposure variables measured with correlated errors in the absence of an internal validation study

F1000Research ◽  
2020 ◽  
Vol 9 ◽  
pp. 1486
Author(s):  
Alexander K. Muoka ◽  
George O. Agogo ◽  
Oscar O. Ngesa ◽  
Henry G. Mwambi
Keyword(s):  
Sensitivity Analysis ◽  
Measurement Error ◽  
Validation Study ◽  
Real Data ◽  
Epidemiological Studies ◽  
Correlated Errors ◽  
Internal Validation ◽  
Multivariate Method ◽  
Multiple Exposures ◽  
Naive Method

Difficulty in obtaining the correct measurement for an individual’s longterm exposure is a major challenge in epidemiological studies that investigate the association between exposures and health outcomes. Measurement error in an exposure biases the association between the exposure and a disease outcome. Usually, an internal validation study is required to adjust for exposure measurement error; it is challenging if such a study is not available. We propose a general method for adjusting for measurement error where multiple exposures are measured with correlated errors (a multivariate method) and illustrate the method using real data. We compare the results from the multivariate method with those obtained using a method that ignores measurement error (the naive method) and a method that ignores correlations between the errors and true exposures (the univariate method). It is found that ignoring measurement error leads to bias and underestimates the standard error. A sensitivity analysis shows that the magnitude of adjustment in the multivariate method is sensitive to the magnitude of measurement error, sign, and the correlation between the errors. We conclude that the multivariate method can be used to adjust for bias in the outcome-exposure association in a case where multiple exposures are measured with correlated errors in the absence of an internal validation study. The method is also useful in conducting a sensitivity analysis on the magnitude of measurement error and the sign of the error correlation.

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