# MFmp: Mitigated fraction from matched pairs In MF: Mitigated Fraction

## Description

Estimates mitigated fraction from matched pairs.

## Usage

 ```1 2``` ``` MFmp(formula=NULL, data=NULL, compare = c("con", "vac"), x=NULL, alpha=0.05, df=NULL, tdist=T) ```

## Arguments

 `formula` Formula of the form ```y ~ x + cluster(w)```, where y is a continuous response, x is a factor with two levels of treatment, and w is a factor indicating the clusters. `data` Data frame `compare` Text vector stating the factor levels - `compare` is the control or reference group to which `compare` is compared `x` Trinomial vector \{Σ I(xy)\} `alpha` Complement of the confidence level. `df` Degrees of freedom. Default N-2 `tdist` Use quantiles of t or Gaussian distribution for confidence interval? Default t distribution.

## Details

Estimates MF from matched pairs by the difference of multinomial fractions (Σ I(x<y) - Σ I(x>y)) / N. The trinomial vector is \{Σ I(x<y), Σ I(x=y), Σ I(x>y)\}

## Value

a `mfmp-class` data object

## Author(s)

David Siev david.siev@aphis.usda.gov

## References

Siev D. (2005). An estimator of intervention effect on disease severity. Journal of Modern Applied Statistical Methods. 4:500–508

`mfmp-class`
 ```1 2``` ```MFmp(les ~ tx + cluster(cage), mlesions, compare = c('con', 'vac')) MFmp(x = c(12, 12, 2)) ```