| estimate {besthr} | R Documentation | 
Perform bootstrap estimation of confidence intervals of ranked HR scores
Description
estimate carries out estimation of bootstrap confidence intervals on
ranked score data. Returns a hrest object of the result
Proceeeds by calculating score ranks, then bootstrapping ranks in non-control
groups retaining the mean for each bootstrap iteration. Calculates
low and high quantiles of bootstrap mean distributions for each group.
If technical replicates are provided in a second grouping column these will
be averaged before proceeding.
Usage
estimate(df, ..., control = "A", nits = 100, low = 0.025, high = 0.975)
Arguments
| df | data frame of score and group data. Contains minimally a score and group column | 
| ... | bare names of columns to use, minimally the score column and the group column in that order. Optionally a third technical replicate column can be provided | 
| control | the value of the grouping column taken to be the control group | 
| nits | the number of bootstap iterations to be done | 
| low | the low probability value of the quantile | 
| high | the high probability value of the quantile | 
Value
a list object of class "hrest"
Examples
 d1 <- make_data()
 estimate(d1, score, group)
 d2 <- make_data2()
 estimate(d2, score_column_name, sample_column_name, rep_column_name )
 d3 <- make_data3()
 estimate(d3, score, sample, rep, nits = 1000)