Description Usage Arguments Details Value Author(s) References
View source: R/interval_auc_2curve.R
Calculates the sample size, AUC's, margin of error, or significance for the confidence interval of the difference of two Areas Under the Curve (AUC). Assumes that the AUCs are based on a single numeric predictor and that the AUCs are normally distributed.
1 2 |
auc1 |
Observed Area Under the Curve 1 (AUC) |
auc2 |
Observed Area Under the Curve 2 AUC) |
n |
Total sample size |
E |
Desired margin of error |
alpha |
Significance Level |
r |
The correlation introduced between the two AUCs by studying the same sample of patients. |
weights |
a list of length-2 vectors giving the
weights for the diseased and non-diseased groups. This
is used to calculate |
optim.max |
Maximum value for |
The ROC curves for this comparison should be based on the
same sample. That is, it should be two tests performed on
the same sample. The comparison assumes some dependence
between the curves, with this dependence being defined by
r
.
Exactly one of the parameters n
, E
,
auc1
, auc2
and alpha
must be passed as
NULL
, and that parameter will be calculated from the
others. Notice that alpha
has a non-NULL
default, so NULL
must be explicitly passed if you
want it computed.
Returns a data frame of the parameters passed to the
function (expanded using expand.grid
) and the
corresponding sample size estimates.
E
: Margin of Error
auc1
: Area Under the Curve 1 (AUC)
auc2
: Area Under the Curve 2 (AUC)
k
:
Proportion of total sample size belonging to group 1
r
: The correlation introduced between the two AUCs
by studying the same sample of patients.
n1_est
: Exact sample size for group 1
n2_est
: Exact sample size for group 2
n_est
: Exact total sample size
n1
:
Estimated sample size for group 1 (next largest integer)
n2
: Estimated sample size for group 2 (next
largest integer)
n
: Estimated total sample
size (sum of n1
and n2
)
Benjamin Nutter
James A Hanley and Barbara J McNeil, "A Method of Comparing the Areas Under Receiver Operating Characteristic Curves Derived from the Same Cases," Radiology, Vol. 148, No. 3, Pages 839-843, September 1983.
Nancy A Obuchowski, "Sample size calculations in studies of test accuracy," Statistical Methods in Medical Research 1998; 7: 371-392
James A. Hanley and Barbara J. McNeil, "The Meaning and Use of the Area under a Receiver Operating Characteristic (ROC) Curve," Radiology. Vol 143. No 1, Pages 29-36, April 1982.
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