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Scales and items with significant AUC statistics may have better than random sensitivity and specificity, but may still be weak predictors.
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Present study focuses an efficient stochastic finite element method for random response sensitivity analysis.
Suspecting that the use of the "don't know" response was not random, a sensitivity analysis was performed to determine how the "don't know" responses could best be incorporated into the analysis approach.
If data are not missing at random, either sensitivity to inclusion/exclusion/imputation will be reported, or selection models will be explored.
In the second, we used the rctmiss command in STATA to conduct a missing not at random (MNAR) sensitivity analysis with the outcome variable in which the largest effect was observed (volume).
However, for comparability with the results for the vaginal delivery outcome, the results we report here are those from the random effects sensitivity analysis, having removed trials at high risk of bias (160 trials included).
Ethnicity, sex and measurement source were also included as level 1 random effects; sensitivity analyses were carried out including these only as fixed effects but the results did not change.
In physics, chaos is defined as behavior so unpredictable as to appear random, allowing great sensitivity to small initial conditions.
We give statistical analysis, sequence random analysis, and sensitivity analysis to plaintext and key on the proposed scheme.
Random effects pooled sensitivity and specificity of CT for distant metastases were 0.52 (95% CI 0.33 0.71) and 0.91 (95% CI 0.86 0.96), respectively.
Using this model, the random cross-validated sensitivity and specificity were 83.3 and 63.4%%, respectively (Table 3b).
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