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Table 2 Sensitivity results for Medium scenario: estimation performance for \(N=50\) observations, \(\dot{z}_i =\) 10,000 reads, and \(T=50\) compositional elements at varying levels of misclassification

From: Analyzing microbiome data with taxonomic misclassification using a zero-inflated Dirichlet-multinomial model

Hyperparameter

\(\beta _{\eta _{t1}} \ne 0\)

\(\beta _{\eta _{t1}} = 0\)

\(\pi _t(\varvec{x}_{ip})\)

Setting

ABS

COV

ABS

COV

ABS

COV

\(\nu _{tt} = 10\)

0.466

0.893

0.302

0.947

0.630

0.560

\(\nu _{tt} = 1000\)

0.904

0.793

0.446

0.982

0.623

0.559

\(\sigma ^2_{\eta } = \sigma ^2_{\gamma }= 1\)

0.440

0.853

0.268

0.954

0.620

0.554

\(\sigma ^2_{\eta } = \sigma ^2_{\gamma }= 10\)

0.514

0.877

0.330

0.930

0.629

0.569

  1. ABS, absolute value of the difference between the estimated and true parameters; COV, 0.95 coverage probabilities