If y2 is provided a bootstrapped procedure is used to compare the correlations between y1 and yhat1 versus
y2 and yhat2. This is achieved by creating two distributions of correlations using bootstrapping; and then
finally compute the distributions overlap.

```
textPredictTest(
y1,
y2,
yhat1,
yhat2,
method = "t-test",
statistic = "correlation",
paired = TRUE,
event_level = "first",
bootstraps_times = 1000,
seed = 6134,
...
)
```

## Arguments

- y1
The observed scores (i.e., what was used to predict when training a model).

- y2
The second observed scores (default = NULL; i.e., for when comparing models that are predicting different
outcomes. In this case a bootstrap procedure is used to create two distributions of correlations that are
compared (see description above).

- yhat1
The predicted scores from model 1.

- yhat2
The predicted scores from model 2 that will be compared with model 1.

- method
Set "t-test" if comparing predictions from models that predict the SAME outcome.
Set "bootstrap" if comparing predictions from models that predict DIFFERENT outcomes or comparison from logistic
regression computing AUC distributions.

- statistic
Character ("correlation", "auc") describing statistic to be compared in bootstrapping.

- paired
Paired test or not in stats::t.test (default TRUE).

- event_level
Character "first" or "second" for computing the auc in the bootstrap.

- bootstraps_times
Number of bootstraps (when providing y2).

- seed
Set seed.

- ...
Settings from stats::t.test or overlapping::overlap (e.g., plot = TRUE).

## Value

Comparison of correlations either a t-test or the overlap of a bootstrapped procedure (see $OV).

## Examples

```
# Example random data
y1 <- runif(10)
yhat1 <- runif(10)
y2 <- runif(10)
yhat2 <- runif(10)
boot_test <- textPredictTest(y1, y2, yhat1, yhat2)
```