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Perhaps the most straightforward way to address possible attenuation bias arising from errors in the measurement of skills is to use two measures of the same concept in an IV approach.
We use two measures of corporate tax avoidance – the reduction in the firm's taxes relative to its pretax accounting income (the long-run cash effective tax rate, Cash ETR) and the tax sheltering measure developed by Wilson.
We use two measures of the diversity of work experiences as our proxies for ( Varleft({H}_{1i}^Oright) ) referred to in equation (3B): OCCUPATIONS i, which represents the number of different occupational experiences since graduation, and INDUSTRIES i, which measures the number of different industries in which those jobs were located9.
We use two measures of explained variation appropriate for binary outcome - direct and indirect [ 16].
We use two measures of subjective well-being: one on happiness and one on life satisfaction.
Here, we use two measures of genetic distance commonly used in the literature: divergence at one mitochondrial gene, and divergence averaged across several nuclear loci.
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We use three measures of classification performance to compare the different methods for cancer gene detection.
We use four measures of conditional conservatism that have also been used in prior studies: (i) Basu's (1997) measure of the sensitivity of earnings to bad news relative to the sensitivity of earnings to good news, (ii) negative non-operating accruals, (iii) how much earnings are skewed, and (iv) a composite measure based on the average rank of the three conditional conservatism measures.
We use three measures of model accuracy as the use of AUC alone might mislead the interpretation given the sensitivity of this measure to spatial autocorrelation [67], [68].
We use three measures of benefits: a reimbursement dummy (binary variable for having received reimbursement), the amount of reimbursement received, and the rate of reimbursement (reimbursement/total cost).
Togouet et al. use five measures of self-reported use, direct observation and interviewer opinion to create a 0-5 score to classify 'non-users,'irregularar users,' and 'regular users' [ 18].
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