MFClus: Clustered mitigated fraction

In MF: Mitigated Fraction

Description

Estimates mitigated fraction from clustered or stratified data.

Usage

  MFClus(formula, data, compare = c("con", "vac"),
    trace.it = FALSE)

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. See Note for handling of input data with more than two levels.
compare	Text vector stating the factor levels - compare[1] is the control or reference group to which compare[2] is compared
trace.it	Verbose tracking of the cycles? Default FALSE.

Details

Averages the U statistic over the clusters and computes MF from it. Clusters are excluded if they do not include both treatments.

Value

a mfcluster-class data object

Note

If input data contains more than two levels of treatment, rows associated with unused treatment levels will be removed.
Factor levels for treatments not present in the input data will be ignored.
Clusters with missing treatments will be excluded. See mfbootcluster-class or use trace.it to identify excluded clusters.

Author(s)

David Siev [e-mail]

References

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

See Also

mfcluster-class

Examples

## Not run: 
MFClus(lesion ~ group + cluster(litter), piglung)

#  Comparing vac to con
#
#  MF = 0.3533835
#
#  By Cluster
#     w  u         r n1 n2         mf
#  U 25 10 0.4000000  5  5 -0.2000000
#  K 12  2 0.2500000  4  2 -0.5000000
#  Z 16 10 0.8333333  3  4  0.6666667
#  D  3  2 1.0000000  1  2  1.0000000
#  N  1  0 0.0000000  1  3 -1.0000000
#  T  8  5 0.8333333  2  3  0.6666667
#  P  4  1 0.5000000  2  1  0.0000000
#  L  3  2 0.6666667  1  3  0.3333333
#  G 15  9 0.7500000  3  4  0.5000000
#  J 15  9 1.0000000  3  3  1.0000000
#  W  6  3 0.7500000  2  2  0.5000000
#  A  9  3 0.3333333  3  3 -0.3333333
#  X 12  6 1.0000000  3  2  1.0000000
#  F 13  7 0.7777778  3  3  0.5555556
#  S 21 11 0.9166667  4  3  0.8333333
#  H 14  8 0.8888889  3  3  0.7777778
#  Y  2  1 1.0000000  1  1  1.0000000
#  E  2  1 1.0000000  1  1  1.0000000
#
#  All
#        w  u         r n1 n2        mf
#  All 181 90 0.6766917 50 52 0.3533835
#
#  Excluded Clusters
#  [1] M, Q, R, B, O, V, I, C

## End(Not run)

MF documentation built on May 2, 2019, 1:46 p.m.