# dprime.SD: d' for Same-different Paradigm In psyphy: Functions for Analyzing Psychophysical Data in R

## Description

Calulate d' for same-different paradigm either assuming a differencing strategy or independent observations

## Usage

 `1` ```dprime.SD(H, FA, zdiff, Pcmax, method = "diff") ```

## Arguments

 `H` numeric in [0, 1] corresponding to Hit rate `FA` numeric in [0, 1] corresponding to False alarm rate `zdiff` numeric. Difference of z-scores for Hit and False Alarm rates ( only valid for method "IO") `Pcmax` numeric in [0, 1]. Proportion correct for an unbiased observer, `pnorm(zdiff)` (only valid for method "IO"). `method` character. Specifies the model to describe the observer's criterion for dividing up the decision space, must be either "diff" for a differencing strategy (the default) or "IO" for independent observations.

## Details

Two different strategies have been described for how the observer partitions the decision space in the same-different paradigm. With Independent Observations, d' can be calculated either from the `H` and `FA` rates, from the difference of z-scores or from the probability correct of an unbiased observer. Only one of these three choices should be specified in the arguments. For the differencing strategy, only the first of these choices is valid.

## Value

Returns the value of d'

## Author(s)

Kenneth Knoblauch

## References

MacMillan, N. A. and Creeman, C. D. (1991) Detection Theory: A User's Guide Cambridge University Press

Green, D. M. and Swets, J. A. (1966) Signal Detection Theory and Psychophysics Robert E. Krieger Publishing Company

`dprime.mAFC`, `dprime.ABX`, `dprime.oddity`

## Examples

 ```1 2 3 4``` ```dprime.SD(H = 0.642, F = 0.3) dprime.SD(H = 0.75, F = 0.3, method = "IO") dprime.SD(zdiff = qnorm(0.75) - qnorm(0.3), method = "IO") dprime.SD(Pcmax = pnorm( (qnorm(0.75) - qnorm(0.3))/2 ), method = "IO") ```

### Example output

```[1] 1.950605
[1] 1.954916
[1] 1.954916
[1] 1.954916
```

psyphy documentation built on Jan. 3, 2022, 5:08 p.m.