Questions tagged [d-prime]
d' (also called sensitivity index) is a measure used in signal detection theory to quantify how well a signal can be distinguished from noise.
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Is there an accepted way to interpret d' (d-prime) for evidence of detection
I have run a learning experiment, with a yes-no familiarity test at the end, and computed d' across various conditions.
Is there some rule of thumb (perhaps dependent on sample size) as to how d' ...
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Can Splithalf Reliability Be Caclulated for an Aggregate Measure?
I have been asked by a journal editor to provide the splithalf reliability for an aggregate dependent variable, d', which is a Signal Detection parameter that captures perceptual sensitivity. However, ...
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d prime with 100% hit rate probability and 0% false alarm probability
I would like to calculate d prime for a memory task that involves detecting old and new items. The problem I have is that some of the subjects have hit rate of 1 and/or false alarm rate of 0, which ...
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Understanding and implementing the dprime measure in Python
According to Wikipedia, the dprime score (aka 'sensitivity index') can be expressed as
$$ d' = Z(\text{hit rate}) - Z(\text{false alarm rate})$$
hit rate (aka recall aka sensitivity) and false alarm ...
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ROC curve, d' A' - assumption-free?
In my research I want to know how reliably certain feature of a sentence indicates the class that sentence belongs to.
So, according to that feature (=how many elements X they contain), the
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d prime correction to use with a low number of trials
I am doing a psycholinguistic experiment, where I want to calculate d’ for each participant’s test scores. In the test, participants listen to 4 familiar words and 8 novel distractor words, and have ...
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How do I calculate d' from experimental data?
In Signal Detection Theory, d' is defined by the z-scores of Hits and False Alarms:
d' = z(Hits) - z(False Alarms).
Say the task is to detect if a certain object is present in a series of pictures, ...
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Connections between $d^\prime$ (d-prime) and AUC (Area Under the ROC Curve); underlying assumptions
In machine learning we may use the area under the ROC curve (often abbreviated AUC, or AUROC) to summarise how well a system can discriminate between two categories. In signal detection theory often ...
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A' (A prime) for extreme Hit rates and False Alarms
I am trying to compute the non parametric measure of sensitivity A' according to the following formula reported by Stanislav & Todorov (1999):
$$
A'= .5+sign(H-F)*((H-F)^2+abs(H-F))/(4*max(H,F)-4*...
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Negative D-prime values; use absolute values?
I have calculated D-prime measurements for for a memory performance task. Subjects viewed images that were either old or new and had to indicate their response via a button press. Thus, their response ...
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Why use d-prime instead of percent correct?
In signal detection theory, people often use $d'$ to assess performance. Apart from the fact that $d'$ is in $z$ units (units of measurement transformed to standard deviation units, i.e., $z$ scores), ...
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Are Cohen's d (effect size) and d prime from the signal detection theory measuring the same thing?
Are d prime (d') in signal detection theory and Cohen's d (mainly reported in the context of the general linear model) measures for the same thing (i.e., the difference of the means in SD-units), and ...
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