Hi,

I used mixed.mdmr() function from r package MDMR to fit a regression model with a distance matrix as the response variable and multiple variables as the fixed effects. And since there are repeated samples from each patient, I used Patient ID as the random effect. My model looks like this:

```
res <- mixed.mdmr(~ treatment + (1|paitnet_ID))
```

To check the result with `summary(res)`

, I got:

```
# Statistic Numer.DF p.value
# Omnibus 2.69 1 0.01078 *
# (Intercept) 3.64 1 0.0014491 **
# treatment 2.74 1 0.009606 **
```

What I need is the percentage of variance explained by the variable "treatment", similar thing to R2 value in a linear regression model. But at least in this package and this function, there is no such value.

Anyone who has used this package can provide some advice on how to get the explained variance from the model? Or if any one knows any package that can do this, please share.

Thanks!

Leran

Thanks for your response! I have no statistics background so a bit hard to figure our the equation you provide with. I just want to find some tools that can allow me to fit this model.