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Area under the curve (AUC)
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The probability that the instrument will yield a higher score for a randomly chosen individual with the target condition than for a randomly chosen individual without the condition
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Area under the graph with sensitivity on the Y axis by one minus specificity on the X axis
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The ideal instrument for screening and/or evaluation of an intervention for children in LAMIC will have a high AUC (close to 1.0). The closer to 0.5 the AUC, the less utility of the screening instrument and the less cost-effectiveness of screening
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Cutoff score
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The score on the instrument chosen to differentiate cases from non-cases; may be chosen to maximize specificity, sensitivity, or both
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Chosen by researcher based on ROC curve
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Based on the type of intervention program, a higher or lower cutoff score could be chosen to prioritize sensitivity or specificity
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Sensitivity
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The ability of an instrument, at a selected cutoff score, to identify persons with a target condition. At a sensitivity of 1.0, all persons with the condition are identified, and there are no false negatives
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Instruments with high sensitivity are ideal to screen children when trying to identify the majority of children in distress needing intervention. At high sensitivity, few children with a condition will be mistakenly deprived of the intervention
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Specificity
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The ability of an instrument to include persons who do not have the target condition below the cutoff score. At a specificity of 1.0, no persons without a target condition score above the cutoff
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Instruments with high specificity minimize the number of children who are incorrectly identified with a high score, but who do not have the target condition. Specificity is a concern when there are negative consequences to being inappropriately included in an intervention, such as stigma or high expense
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Positive predictive value (PPV)
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The proportion of persons with scores above cutoff who are correctly classified as having the target condition compared to all persons who score above the cutoff
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PPV produces more accurate cost estimates of improperly including participants than specificity alone because of accounting for prevalence of a condition in the target population
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Negative predictive value (NPV)
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The proportion of persons who score below the selected cutoff who do not have the target condition compared to all persons below the cutoff
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NPV is used to determine the proportion improperly excluded from an intervention, taking prevalence into account. NPV helps to estimate the cost of not including a proportion of children in an intervention
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Reliability (Cronbach's alpha)
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A measures of internal consistency based on the degree of inter-correlation among all items on a scale
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Reliability is important for newly developed measures or adapted measures in LAMIC to help identify items that may not be culturally or contextually relevant, such as stomachaches in Nepal
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is the average of all covariances between the components, and 
is the average variance.
is the average of all covariances between the components, and 
is the average variance.