analyze {adestr} | R Documentation |

## Analyze a dataset

### Description

The `analyze`

function can be used calculate the values of a list of
point estimators,
confidence intervals,
and p-values for a given dataset.

### Usage

```
analyze(
data,
statistics = list(),
data_distribution,
use_full_twoarm_sampling_distribution = FALSE,
design,
sigma,
exact = FALSE
)
## S4 method for signature 'data.frame'
analyze(
data,
statistics = list(),
data_distribution,
use_full_twoarm_sampling_distribution = FALSE,
design,
sigma,
exact = FALSE
)
```

### Arguments

`data` |
a data.frame containing the data to be analyzed. |

`statistics` |
a list of objects of class |

`data_distribution` |
object of class |

`use_full_twoarm_sampling_distribution` |
logical indicating whether this estimator is intended to be used with the full sampling distribution in a two-armed trial. |

`design` |
object of class |

`sigma` |
assumed standard deviation. |

`exact` |
logical indicating usage of exact n2 function. |

### Details

Note that in `adestr`

, statistics are codes as functions of the
stage-wise sample means (and stage-wise sample variances if data_distribution is
`Student`

). In a first-step, the data is summarized to produce these
parameters. Then, the list of statistics are evaluated at the values of these parameters.

The output of the `analyze`

function also displays information on the hypothesis
test and the interim decision. If the `statistics`

list is empty, this will
be the only information displayed.

### Value

`Results`

object containing the values of the statistics
when applied to data.

### Examples

```
set.seed(123)
dat <- data.frame(
endpoint = c(rnorm(28, 0.3)),
stage = rep(1, 28)
)
analyze(data = dat,
statistics = list(),
data_distribution = Normal(FALSE),
design = get_example_design(),
sigma = 1)
# The results suggest recruiting 32 patients for the second stage
dat <- rbind(
dat,
data.frame(
endpoint = rnorm(32, mean = 0.3),
stage = rep(2, 32)))
analyze(data = dat,
statistics = get_example_statistics(),
data_distribution = Normal(FALSE),
design = get_example_design(),
sigma = 1)
```

*adestr*version 0.5.0 Index]