Mitigated fraction from matched pairs

Estimates mitigated fraction from matched pairs.

Usage

MFmp(
  formula = NULL,
  data = NULL,
  compare = c("con", "vac"),
  x = NULL,
  alpha = 0.05,
  df = NA,
  tdist = TRUE
)

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[1] is the control or reference group to which compare[2] is compared
x: Trinomial vector \(\{\Sigma I(x < y), \Sigma I(x = y), \Sigma I(x > y)\}\)
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.

Value

a mfmp data object

Details

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

Note

upper confidence interval is truncated to 1; lower confidence interval is truncated to -1. Point estimate of 1.0 indicates complete separation.

References

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

Author

MF-package

Examples

MFmp(les ~ tx + cluster(cage), mlesions, compare = c("con", "vac"))
#> 95% t intervals on 24 df
#>  
#>     point     lower     upper 
#> 0.3846154 0.1316679 0.6375628 
MFmp(x = c(12, 12, 2))
#> 95% t intervals on 24 df
#>  
#>     point     lower     upper 
#> 0.3846154 0.1316679 0.6375628