runDAcc: Perform meta-analysis of diagnostic accuracy data using the...
In RichardBirnie/mautils: Utilities to facilitate an automated workflow for meta-analysis
Description
Perform meta-analysis of diagnostic accuracy data using the Reitsma bivariate
model
Usage
1
Arguments
df
A data frame with a column of study IDs and integer variables for
observed frequencies of true positives, false negatives, false positives
and true negatives. The names of the columns should be StudyID, TP, FN, FP
and TN.
file
A character string specifying the base directory for the
analysis. This function will create a subdirectory 'Results' within this
directory will be a 'Figures' subdirectory.
test_id
A character string indicating the identity of the diagnostic
test
analysis_case
A character string indicating a short name that
identifies this analysis. This is used in filenames so keep it short.
RichardBirnie/mautils documentation built on July 12, 2019, 8:56 p.m.
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Description
Perform meta-analysis of diagnostic accuracy data using the Reitsma bivariate model
Usage
1 |
Arguments
df |
A data frame with a column of study IDs and integer variables for observed frequencies of true positives, false negatives, false positives and true negatives. The names of the columns should be StudyID, TP, FN, FP and TN. |
file |
A character string specifying the base directory for the analysis. This function will create a subdirectory 'Results' within this directory will be a 'Figures' subdirectory. |
test_id |
A character string indicating the identity of the diagnostic test |
analysis_case |
A character string indicating a short name that identifies this analysis. This is used in filenames so keep it short. |
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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