Table 1.
Empirical Type I Errors for MiRKAT and Optimal MiRKAT with Continuous Outcome
Simulation Setup | n |
Empirical Type I Errors |
||||||||
---|---|---|---|---|---|---|---|---|---|---|
Kw | Ku | KBC | K0 | K0.25 | K0.5 | K0.75 | Koptimal | |||
Simulation Scenario 1: Clustered OTUs | ||||||||||
, no adjustment for X | 100 | 0.053 | 0.050 | 0.050 | 0.046 | 0.047 | 0.048 | 0.052 | 0.050 | 0.023 |
200 | 0.052 | 0.047 | 0.051 | 0.053 | 0.049 | 0.048 | 0.051 | 0.051 | 0.026 | |
, adjustment for X | 100 | 0.056 | 0.048 | 0.047 | 0.049 | 0.045 | 0.050 | 0.048 | 0.046 | 0.024 |
200 | 0.051 | 0.050 | 0.053 | 0.048 | 0.047 | 0.052 | 0.049 | 0.050 | 0.027 | |
X![]() |
100 | 0.389∗ | 0.062∗ | 0.172∗ | 0.268∗ | 0.345∗ | 0.384∗ | 0.182∗ | 0.268∗ | 0.183∗ |
200 | 0.790∗ | 0.080∗ | 0.398∗ | 0.587∗ | 0.732∗ | 0.791∗ | 0.387∗ | 0.651∗ | 0.547∗ | |
X![]() |
100 | 0.055 | 0.047 | 0.047 | 0.049 | 0.046 | 0.049 | 0.046 | 0.049 | 0.024 |
200 | 0.052 | 0.049 | 0.051 | 0.047 | 0.047 | 0.052 | 0.050 | 0.049 | 0.026 | |
Simulation Scenario 2: Top Ten OTUs | ||||||||||
, no adjustment for X | 100 | 0.053 | 0.050 | 0.050 | 0.045 | 0.048 | 0.049 | 0.053 | 0.050 | 0.025 |
200 | 0.051 | 0.047 | 0.050 | 0.053 | 0.050 | 0.047 | 0.051 | 0.050 | 0.026 | |
, adjustment for X | 100 | 0.056 | 0.048 | 0.047 | 0.050 | 0.046 | 0.051 | 0.047 | 0.049 | 0.021 |
200 | 0.051 | 0.049 | 0.053 | 0.047 | 0.047 | 0.052 | 0.050 | 0.051 | 0.023 | |
X![]() |
100 | 0.153∗ | 0.048∗ | 0.669∗ | 0.105∗ | 0.124∗ | 0.147∗ | 0.157∗ | 0.516∗ | 0.067∗ |
200 | 0.307∗ | 0.048∗ | 0.976∗ | 0.194∗ | 0.239∗ | 0.293∗ | 0.320∗ | 0.932∗ | 0.151∗ | |
X![]() |
100 | 0.056 | 0.048 | 0.047 | 0.049 | 0.046 | 0.050 | 0.047 | 0.049 | 0.020 |
200 | 0.052 | 0.049 | 0.051 | 0.048 | 0.048 | 0.051 | 0.049 | 0.049 | 0.024 |
Type I error was evaluated for scenarios in which additional covariates were independent of the OTUs or related to the OTUs (XZ) with the use of 5,000 simulated datasets. Kw, Ku, KBC, K0, K0.25, K0.5, and K0.75 represent MiRKAT results for the weighted UniFrac kernel, unweighted UniFrac kernel, Bray-Curtis kernel, and generalized UniFrac kernels with α = 0, 0.25, 0.5, and 0.75, respectively. Koptimal represents the simulation results for optimal MiRKAT considering all seven kernels, and shows the results for a naive Bonferroni-adjusted test. The p values for optimal MiRKAT were obtained by 1,000 permutations. ∗Inflated type I error.