View source: R/prevalence_calc.R
post_hoc_est_scc | R Documentation |
This function provides probabilistic statements about the composition of a sample after application of a certain test procedure within SCC. For this purpose a Binomial distribution is used.
post_hoc_est_scc( combination_method, A_threshold, B_threshold, C_threshold, switch_to_target, devices, target_selfreported, target_tested, min_number = NULL, min_prob = NULL )
combination_method |
Number (1 to 18) corresponding to the test method. |
A_threshold |
(scalar integer) Threshold for Test A (1 to 6). |
B_threshold |
(scalar integer) Threshold for Test B (1 to 6). |
C_threshold |
(scalar integer) Threshold for Test C (1 to 6). |
switch_to_target |
Sets the (estimated) switching prevalence. The switching prevalence describes the probability that a participant who indicates the use of a device other than the target device actually switches to the target device after being prompted to do so. |
devices |
Sets the desired playback device. Possible settings are
|
target_selfreported |
Number of participants who reported the use of the target device. |
target_tested |
Number of participants who reported the use of a playback device other than the target device and got a test result indicating the use of the target device. |
min_number |
minimum number of participants |
min_prob |
(greater than 0, less than 1) for the event that
at least an unknown number of participants |
Within SCC the final sample contains participants who reported the use of
the target playback device and participants who did not do so but got a
test result indicating the use of the target device.
Given a test procedure, switching prevalence, the number of participants who
reported the use of the target playback device, and the number of
participants who reported the use of a device other than the target device
and got a test result indicating the use of the target device the event that
at least k
participants who are in the final sample used the correct
device is considered.
The function either calculates the minimum probability for this event for a
given k
or k
for a given probability for this event.
Only one of the arguments min_number
and min_prob
can be
used.
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