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Short answer
To me, it seems perfectly feasible to use deltaE both as dependent and independent variable of color difference.

Background
DeltaE (Fig. 1) can be used to generate the target stimuli by pre-selecting a set of different color pairs to use in the recall task (method-of-constant stimuli, MOC), or alternatively, by using different step sizes of deltaE along the color matching test (in case of an adaptive staircase procedure for instance). It will depend on the study setup what specific method one wishes to use (MOC or an adaptive test).

On the other hand, deltaE can very well be used during data analysis to determine the difference between the presented color and the subject's response to that color. The advantage of using a single number (deltaE) over, e.g., RGB values is that deltaE is a single number (i.e. an angle) and can hence be straightforwardly used as an outcome measure, whereas RGB values would have to be recoded along three axes and somehow transformed into a single number representing response error.

^{Fig. 1. Color wheel. source: Nguyen et al. (2018)}

<sub>Reference
- Nguyen et al., BioResources (2018); 13(3), 6250-64</sub>

Short answer
To me, it seems perfectly feasible to use deltaE both as dependent and independent variable of color difference.

Background
DeltaE (Fig. 1) can be used to generate the target stimuli by pre-selecting a set of different color pairs to use in the recall task (method-of-constant stimuli, MOC), or alternatively, by using different step sizes of deltaE along the color matching test (in case of an adaptive staircase procedure for instance). It will depend on the study setup what specific method one wishes to use (MOC or an adaptive test).

On the other hand, deltaE can very well be used during data analysis to determine the difference between the presented color and the subject's response to that color. The advantage of using a single number (deltaE) over, e.g., RGB values is that deltaE is a single number (i.e. an angle) and can hence be straightforwardly used as an outcome measure, whereas RGB values would have to be recoded along three axes and somehow transformed into a single number representing response error.

^{Fig. 1. Color wheel. source: Nguyen et al. (2018)}

<sub>Reference
- Nguyen et al., BioResources (2018); 13(3), 6250-64</sub>

To me, it seems perfectly feasible to use deltaE both as dependent and independent variable of color difference.

DeltaE (Fig. 1) can be used to generate the target stimuli by pre-selecting a set of different color pairs to use in the recall task (method-of-constant stimuli, MOC), or alternatively, by using different step sizes of deltaE along the color matching test (in case of an adaptive staircase procedure for instance). It will depend on the study setup what specific method one wishes to use (MOC or an adaptive test).

On the other hand, deltaE can very well be used during data analysis to determine the difference between the presented color and the subject's response to that color. The advantage of using a single number (deltaE) over, e.g., RGB values is that deltaE is a single number (i.e. an angle) and can hence be straightforwardly used as an outcome measure, whereas RGB values would have to be recoded along three axes and somehow transformed into a single number representing response error.

^{Fig. 1. Color wheel. source: Nguyen et al. (2018)}

<sub>Reference
- Nguyen et al., BioResources (2018); 13(3), 6250-64</sub>

Short answer
To me, it seems perfectly feasible to use deltaE both as dependent and independent variable of color difference.

Background
DeltaE (Fig. 1) can be used to generate the target stimuli by pre-selecting a set of different color pairs to use in the recall task (method-of-constant stimuli, MOC), or alternatively, by using different step sizes of deltaE along the color matching test (in case of an adaptive staircase procedure for instance). It will depend on the study setup what specific method one wishes to use (MOC or an adaptive test).

On the other hand, deltaE can very well be used during data analysis to determine the difference between the presented color and the subject's response to that color. The advantage of using a single number (deltaE) over, e.g., RGB values is that deltaE is a single number (i.e. an angle) and can hence be straightforwardly used as an outcome measure, whereas RGB values would have to be recoded along three axes and somehow transformed into a single number representing response error.

^{Fig. 1. Color wheel. source: Nguyen et al. (2018)}

<sub>Reference
- Nguyen et al., BioResources (2018); 13(3), 6250-64</sub>

To me, it seems perfectly feasible to use deltaE both as dependent and independent variable of color difference.

DeltaE can be used to generate the target stimuli by pre-selecting a set of different color pairs to use in the recall task (method-of-constant stimuli, MOC), or alternatively, by using different step sizes of deltaE along the color matching test (in case of an adaptive staircase procedure for instance). It will depend on the study setup what specific method one wishes to use (MOC or an adaptive test).

On the other hand, deltaE can very well be used during data analysis to determine the difference between the presented color and the subject's response to that color. The advantage of using a single number (deltaE) over, e.g., RGB values is that deltaE is a single number (i.e. an angle) and can hence be straightforwardly used as an outcome measure, whereas RGB values would have to be recoded along three axes and somehow transformed into a single number representing response error.

To me, it seems perfectly feasible to use deltaE both as dependent and independent variable of color difference.

DeltaE (Fig. 1) can be used to generate the target stimuli by pre-selecting a set of different color pairs to use in the recall task (method-of-constant stimuli, MOC), or alternatively, by using different step sizes of deltaE along the color matching test (in case of an adaptive staircase procedure for instance). It will depend on the study setup what specific method one wishes to use (MOC or an adaptive test).

On the other hand, deltaE can very well be used during data analysis to determine the difference between the presented color and the subject's response to that color. The advantage of using a single number (deltaE) over, e.g., RGB values is that deltaE is a single number (i.e. an angle) and can hence be straightforwardly used as an outcome measure, whereas RGB values would have to be recoded along three axes and somehow transformed into a single number representing response error.

^{Fig. 1. Color wheel. source: Nguyen et al. (2018)}

<sub>Reference
- Nguyen et al., BioResources (2018); 13(3), 6250-64</sub>