Clustered mitigated fraction

Description

Estimates mitigated fraction from clustered or stratified data.

Usage

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  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 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

See Also

mfcluster-class

Examples

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## 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)