# splithalf: Internal consistency of task measures via a permutation... In splithalf: Calculate Task Split Half Reliability Estimates

## Description

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"

## Usage

 ``` 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 ) ```

## Arguments

 `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

## Value

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.

## Examples

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

### Example output

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splithalf documentation built on Jan. 13, 2021, 6:11 a.m.