Description Usage Arguments Value Examples

This function calculates split half reliability estimates via a permutation approach for a wide range of tasks The (unofficial) version name is "This function gives me the power to fight like a crow"

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 | ```
splithalf(
data,
outcome = "RT",
score = "difference",
conditionlist = FALSE,
halftype = "random",
permutations = 5000,
var.RT = "latency",
var.ACC = "accuracy",
var.condition = FALSE,
var.participant = "subject",
var.trialnum = "trialnum",
var.compare = "congruency",
compare1 = "Congruent",
compare2 = "Incongruent",
average = "mean",
plot = FALSE,
round.to = 2
)
``` |

`data` |
specifies the raw dataset to be processed |

`outcome` |
indicates the type of data to be processed, e.g. response time or accuracy rates |

`score` |
indicates how the outcome score is calculated, e.g. most commonly the difference score between two trial types. Can be "average", "difference", "difference_of_difference", and "DPrime" |

`conditionlist` |
sets conditions/blocks to be processed |

`halftype` |
specifies the split method; "oddeven", "halfs", or "random" |

`permutations` |
specifies the number of random splits to run - 5000 is good |

`var.RT` |
specifies the RT variable name in data |

`var.ACC` |
specifiec the accuracy variable name in data |

`var.condition` |
specifies the condition variable name in data - if not specified then splithalf will treat all trials as one condition |

`var.participant` |
specifies the subject variable name in data |

`var.trialnum` |
specifies the trial number variable |

`var.compare` |
specified the variable that is used to calculate difference scores (e.g. including congruent and incongruent trials) |

`compare1` |
specifies the first trial type to be compared (e.g. congruent trials) |

`compare2` |
specifies the first trial type to be compared (e.g. incongruent trials) |

`average` |
use mean or median to calculate average scores? |

`plot` |
gives the option to visualise the estimates in a raincloud plot. defaults to FALSE |

`round.to` |
sets the number of decimals to round the estimates to defaults to 2 |

Returns a data frame containing permutation based split-half reliability estimates

splithalf is the raw estimate of the bias index

spearmanbrown is the spearman-brown corrected estimate of the bias index

Warning: If there are missing data (e.g one condition data missing for one participant) output will include details of the missing data and return a dataframe containing the NA data. Warnings will be displayed in the console.

1 | ```
## see online documentation for examples
``` |

```
```

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