estimateAUCandStdErr {BLOQ} | R Documentation |

## Estimate AUC and its standard error

### Description

function to estimate AUC and compute standard error of this estimate

### Usage

```
estimateAUCandStdErr(
imputedData,
timePoints,
isMultiplicative = FALSE,
na.rm = FALSE
)
```

### Arguments

`imputedData` |
numeric matrix or data frame of size n by J (n the sample size and J the number of time points) |

`timePoints` |
vector of time points |

`isMultiplicative` |
logical variable indicating whether an additive error model (FALSE) or a multiplicative error model (TRUE) should be used |

`na.rm` |
logical variable indicating whether the rows with missing values should be ignored or not. |

### Value

vector of length 2 with estimated AUC and its standard error

### Author(s)

Vahid Nassiri, Helen Yvette Barnett

### Examples

```
# generate data from Beal model with only fixed effects
set.seed(111)
genDataFixedEffects <- simulateBealModelFixedEffects(10, 0.693,
+ 1, 1, seq(0.5,3,0.5))
# Impute the data with BLOQ's with one of the provided methods,
# for example, here we use ROS
imputedDataROS <- imputeROS(genDataFixedEffects, 0.1)
# estimate AUC and its standard error
estimateAUCandStdErr(imputedDataROS,seq(0.5,3,0.5))
```

[Package

*BLOQ*version 0.1-1 Index]