I need some help in interpreting some STATA output which is quoting AIC/BIC. Effectively, I am using MIDAS to pool some sensitivity and specificity values for different cutoffs on a diagnostic test. Alas sensitivity and specificity may vary not only dependent on the cutoff but also due to variation in the background vaccination rate for a related condition.
I have generated the following output from midas, which quotes BIC and AIC for the contribution of the variable 'vaccrate'. Could anyone help me interpret whether this could be considered as a significant contribution or not?
Estimating Covariate Effect Of: vaccrate
Sensitivity and Specificity
Joint Model
SUMMARY DATA AND PERFORMANCE ESTIMATES
Number of studies = 18
Reference-positive Units = 6185
Reference-negative Units = 625
Pretest Prob of Disease = 0.91
Deviance = 263.5
AIC = 273.5
BIC = 281.4
BICdiff = 657.1
Correlation (Mixed Model)= -0.90
Proportion of heterogeneity likely due to threshold effect = 0.80
Interstudy variation in Sensitivity: ICC_SEN = 0.17, 95% CI = [ 0.05- 0.29]
Interstudy variation in Sensitivity: MED_SEN = 0.68, 95% CI = [ 0.62- 0.77]
Interstudy variation in Specificity: ICC_SPE = 0.20, 95% CI = [ 0.09- 0.31]
Interstudy variation in Specificity: MED_SPE = 0.70, 95% CI = [ 0.65- 0.77]
ROC Area, AUROC = 0.84 [0.80 - 0.87]
Heterogeneity (Chi-square): LRT_Q = 246.886, df =2.00, LRT_p =0.000
Inconsistency (I-square): LRT_I2 = 99, 95% CI = [ 99-100]
Parameter Estimate 95% CI
Sensitivity 0.69 [ 0.59, 0.78]
Specificity 0.84 [ 0.77, 0.89]
Positive Likelihood Ratio 4.3 [ 3.3, 5.7]
Negative Likelihood Ratio 0.37 [ 0.29, 0.47]
Diagnostic Odds Ratio 12 [ 9, 16]