# Xdc.sevsample: Likelihood-Ratio-Test Statistics: Several Sample... In HMP: Hypothesis Testing and Power Calculations for Comparing Metagenomic Samples from HMP

## Description

This routine provides the value of the Likelihood-Ratio-Test Statistics and the corresponding p-value for evaluating the several sample Dirichlet-Multinomial parameter test comparison.

## Usage

 1 Xdc.sevsample(group.data, epsilon = 10^(-4), est = "mom") 

## Arguments

 group.data A list where each element is a matrix of taxonomic counts(columns) for each sample(rows). (See Notes 1 and 2 in details) epsilon Convergence tolerance. To terminate, the difference between two succeeding log-likelihoods must be smaller than epsilon. Default value is 10^(-4). est The type of parameter estimator to be used with the Likelihood-ratio-test statistics, 'mle' or 'mom'. Default value is 'mom'. (See Note 3 in details)

## Details

To assess whether the Dirichlet parameter vector, \mathbf{α}_{\mathrm{m}}=\mathbf{π}_{\mathrm{m}} \frac{1-θ_{\mathrm{m}}}{θ_{\mathrm{m}}}(a function of the RAD probability-mean vector and overdispersion), observed in J groups of microbiome samples are equal to each other, the following hypothesis \mathrm{H}_{\mathrm{o}}: \mathbf{α}_{\mathrm{1}} = \cdots =\mathbf{α}_{\mathrm{m}}=\cdots= \mathbf{α}_{\mathrm{J}}=\mathbf{α}_{\mathrm{o}} versus \mathrm{H}_{\mathrm{a}}: \mathbf{α}_{\mathrm{m}} \ne \mathbf{α}_{\mathrm{o}}, m=1, …, J can be tested. The null hypothesis implies that the HMP samples across groups have the same mean and overdispersion, indicating that the RAD models are identical. In particular, the likelihood-ratio test statistic is used, which is given by,

x_{\mathrm{dc}}=-2 \log≤ft\{\frac{L≤ft(\mathbf{α}_{\mathrm{o}}; \mathbf{X}_{\mathrm{1}},…, \mathbf{X}_{\mathrm{J}} \right)}{L≤ft(\mathbf{α}_{\mathrm{1}},…,\mathbf{α}_{\mathrm{J}}; \mathbf{X}_{\mathrm{1}},…, \mathbf{X}_{\mathrm{J}} \right)}\right\}.

The asymptotic null distribution of x_{\mathrm{dc}} follows a Chi-square with degrees of freedom equal to (J-1)*K, where K is the number of taxa (Wilks, 1938).

1. Note 1: The matrices in group.data must contain the same taxa, in the same order.

2. Note 2: Each taxa should be present in at least 1 sample, a column with all 0's may result in errors and/or invalid results.

3. Note 3: 'mle' will take significantly longer time and may not be optimal for small sample sizes; 'mom' will provide more conservative results in such a case.

## Value

A list containing the Xdc statistics and p-value.

## Author(s)

Patricio S. La Rosa, Elena Deych, Berkley Shands, William D. Shannon

## References

Wilks, S. S. (1938). The Large-Sample Distribution of the Likelihood Ratio for Testing Composite Hypotheses. The Annals of Mathematical Statistics 9, 60-62.

## Examples

 1 2 3 4 5 6  data(saliva) data(throat) ### A test where we use the default values for initscalar and epsilon xdc.sev_check <- Xdc.sevsample(list(saliva, throat)) xdc.sev_check 

HMP documentation built on May 29, 2017, 11:52 a.m.

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