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)
```

*besthr*version 0.3.2 Index]