| cond_false | R Documentation |
cond_false is a frequency that describes the
number of individuals in the current population N
for which the condition is FALSE (i.e., actually false cases).
cond_false
An object of class numeric of length 1.
Key relationships:
to probabilities:
The frequency of cond_false individuals depends on the population size N and
the complement of the condition's prevalence 1 - prev and is split further into two subsets of
fa by the false alarm rate fart and
cr by the specificity spec.
Perspectives:
by condition:
The frequency cond_false is determined by the population size N times the complement of the prevalence (1 - prev):
cond_false= N x (1 - prev)
by decision:
a. The frequency fa is determined by cond_false times the false alarm rate fart = (1 - spec)
(aka. FPR):
fa = cond_false x fart = cond_false x (1 - spec)
b. The frequency cr is determined by cond_false times the specificity spec = (1 - fart):
cr = cond_false x spec = cond_false x (1 - fart)
to other frequencies:
In a population of size N the following relationships hold:
N = cond_true + cond_false (by condition)
N = dec_pos + dec_neg (by decision)
N = dec_cor + dec_err (by correspondence of decision to condition)
N = hi + mi + fa + cr (by condition x decision)
Current frequency information is computed by
comp_freq and contained in a list
freq.
Consult Wikipedia: Confusion matrix for additional information.
is_freq verifies frequencies;
num contains basic numeric parameters;
init_num initializes basic numeric parameters;
freq contains current frequency information;
comp_freq computes current frequency information;
prob contains current probability information;
comp_prob computes current probability information.
Other frequencies:
N,
cond_true,
cr,
dec_cor,
dec_err,
dec_neg,
dec_pos,
fa,
hi,
mi
cond_false <- 1000 * .90 # => sets cond_false to 90% of 1000 = 900 cases.
is_freq(cond_false) # => TRUE
is_prob(cond_false) # => FALSE, as cond_false is no probability [but (1 - prev) and spec are]
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