computeBias: Compute bias (over/underconfidence) for each participant.
In drsimonj/jacksonphd: Data from Simon A Jackson's PhD (2016)
Description
Usage
Arguments
Value
Examples
Description
Compute the bias score for each participant in the data frame.
To be called with compute().
Usage
1
computeBias(x, group = c(T), na.rm = TRUE)
Arguments
x
Data frame from phd sample.
group
Logical vector used to return a group of the candidate results.
See ?getCol for details.
na.rm
logical. Should missing values (including NaN) be omitted from the calculations? Default = True
Value
Bias vector.
Examples
1
computeBias(phd[[1]]$EA)
drsimonj/jacksonphd documentation built on May 15, 2019, 2:52 p.m.
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Description Usage Arguments Value Examples
Description
Compute the bias score for each participant in the data frame. To be called with compute().
Usage
1 | computeBias(x, group = c(T), na.rm = TRUE)
|
Arguments
x |
Data frame from phd sample. |
group |
Logical vector used to return a group of the candidate results. See ?getCol for details. |
na.rm |
logical. Should missing values (including NaN) be omitted from the calculations? Default = True |
Value
Bias vector.
Examples
1 | computeBias(phd[[1]]$EA)
|
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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