comp_prob
computes current probability information
from 3 essential probabilities
(prev
,
sens
or mirt
,
spec
or fart
).
It returns a list of 13 key probabilities prob
as its output.
comp_prob(
prev = num$prev,
sens = num$sens,
mirt = NA,
spec = num$spec,
fart = NA,
tol = 0.01
)
The condition's prevalence value prev
(i.e., the probability of the condition being TRUE
).
The decision's sensitivity value sens
(i.e., the conditional probability of a positive decision
provided that the condition is TRUE
).
sens
is optional when its complement mirt
is provided.
The decision's miss rate value mirt
(i.e., the conditional probability of a negative decision
provided that the condition is TRUE
).
mirt
is optional when its complement sens
is provided.
The decision's specificity value spec
(i.e., the conditional probability
of a negative decision provided that the condition is FALSE
).
spec
is optional when its complement fart
is provided.
The decision's false alarm rate fart
(i.e., the conditional probability
of a positive decision provided that the condition is FALSE
).
fart
is optional when its complement spec
is provided.
A numeric tolerance value for is_complement
.
Default: tol = .01
.
A list prob
containing 13 key probability values.
comp_prob
assumes that a sufficient and
consistent set of essential probabilities
(i.e., prev
and
either sens
or its complement mirt
, and
either spec
or its complement fart
)
is provided.
comp_prob
computes and returns a full set of basic and
various derived probabilities (e.g.,
the probability of a positive decision ppod
,
the probability of a correct decision acc
,
the predictive values PPV
and NPV
, as well
as their complements FDR
and FOR
)
in its output of a list prob
.
Extreme probabilities (sets containing two or more
probabilities of 0 or 1) may yield unexpected values
(e.g., predictive values PPV
or NPV
turning NaN
when is_extreme_prob_set
evaluates to TRUE
).
comp_prob
is the probability counterpart to the
frequency function comp_freq
.
Key relationships between probabilities and frequencies:
Three perspectives on a population:
A population of N
individuals can be split into 2 subsets of frequencies
in 3 different ways:
by condition:
N = cond_true + cond_false
The frequency cond_true
depends on the prevalence prev
and
the frequency cond_false
depends on the prevalence's complement 1 - prev
.
by decision:
The frequency dec_pos
depends on the proportion of positive decisions ppod
and
the frequency dec_neg
depends on the proportion of negative decisions 1 - ppod
.
by accuracy (i.e., correspondence of decision to condition):
Each perspective combines 2 pairs of the 4 essential probabilities (hi, mi, fa, cr).
When providing probabilities, the population size N
is a free parameter (independent of the
essential probabilities prev
, sens
, and spec
).
If N
is unknown (NA
), a suitable minimum value can be computed by comp_min_N
.
Defining probabilities in terms of frequencies:
Probabilities are -- determine, describe, or are defined as -- the relationships between frequencies. Thus, they can be computed as ratios between frequencies:
prevalence prev
:
sensitivity sens
:
miss rate mirt
:
specificity spec
:
false alarm rate fart
:
proportion of positive decisions ppod
:
positive predictive value PPV
:
negative predictive value NPV
:
false detection rate FDR
:
false omission rate FOR
:
accuracy acc
:
rate of hits, given accuracy p_acc_hi
:
rate of false alarms, given inaccuracy p_err_fa
:
Note: When frequencies are rounded (by round = TRUE
in comp_freq
),
probabilities computed from freq
may differ from exact probabilities.
Functions translating between representational formats:
comp_prob_prob
, comp_prob_freq
,
comp_freq_prob
, comp_freq_freq
(see documentation of comp_prob_prob
for details).
prob
contains current probability information;
accu
contains current accuracy information;
num
contains basic numeric parameters;
init_num
initializes basic numeric parameters;
pal
contains current color information;
txt
contains current text information;
freq
contains current frequency information;
comp_freq
computes frequencies from probabilities;
is_valid_prob_set
verifies sets of probability inputs;
is_extreme_prob_set
verifies sets of extreme probabilities;
comp_min_N
computes a suitable minimum population size N
;
comp_freq_freq
computes current frequency information from (4 essential) frequencies;
comp_freq_prob
computes current frequency information from (3 essential) probabilities;
comp_prob_freq
computes current probability information from (4 essential) frequencies;
comp_prob_prob
computes current probability information from (3 essential) probabilities.
Other functions computing probabilities:
comp_FDR()
,
comp_FOR()
,
comp_NPV()
,
comp_PPV()
,
comp_accu_freq()
,
comp_accu_prob()
,
comp_acc()
,
comp_comp_pair()
,
comp_complement()
,
comp_complete_prob_set()
,
comp_err()
,
comp_fart()
,
comp_mirt()
,
comp_ppod()
,
comp_prob_freq()
,
comp_sens()
,
comp_spec()
# Basics:
comp_prob(prev = .11, sens = .88, spec = .77) # => ok: PPV = 0.3210614
#> $prev
#> [1] 0.11
#>
#> $sens
#> [1] 0.88
#>
#> $mirt
#> [1] 0.12
#>
#> $spec
#> [1] 0.77
#>
#> $fart
#> [1] 0.23
#>
#> $ppod
#> [1] 0.3015
#>
#> $PPV
#> [1] 0.3210614
#>
#> $FDR
#> [1] 0.6789386
#>
#> $NPV
#> [1] 0.9811024
#>
#> $FOR
#> [1] 0.01889764
#>
#> $acc
#> [1] 0.7821
#>
#> $p_acc_hi
#> [1] 0.1237693
#>
#> $p_err_fa
#> [1] 0.9394218
#>
comp_prob(prev = .11, sens = NA, mirt = .12, spec = NA, fart = .23) # => ok: PPV = 0.3210614
#> $prev
#> [1] 0.11
#>
#> $sens
#> [1] 0.88
#>
#> $mirt
#> [1] 0.12
#>
#> $spec
#> [1] 0.77
#>
#> $fart
#> [1] 0.23
#>
#> $ppod
#> [1] 0.3015
#>
#> $PPV
#> [1] 0.3210614
#>
#> $FDR
#> [1] 0.6789386
#>
#> $NPV
#> [1] 0.9811024
#>
#> $FOR
#> [1] 0.01889764
#>
#> $acc
#> [1] 0.7821
#>
#> $p_acc_hi
#> [1] 0.1237693
#>
#> $p_err_fa
#> [1] 0.9394218
#>
comp_prob() # => ok, using current defaults
#> $prev
#> [1] 0.25
#>
#> $sens
#> [1] 0.85
#>
#> $mirt
#> [1] 0.15
#>
#> $spec
#> [1] 0.75
#>
#> $fart
#> [1] 0.25
#>
#> $ppod
#> [1] 0.4
#>
#> $PPV
#> [1] 0.53125
#>
#> $FDR
#> [1] 0.46875
#>
#> $NPV
#> [1] 0.9375
#>
#> $FOR
#> [1] 0.0625
#>
#> $acc
#> [1] 0.775
#>
#> $p_acc_hi
#> [1] 0.2741935
#>
#> $p_err_fa
#> [1] 0.8333333
#>
length(comp_prob()) # => 13 probabilities
#> [1] 13
# Ways to work:
comp_prob(.99, sens = .99, spec = .99) # => ok: PPV = 0.999898
#> $prev
#> [1] 0.99
#>
#> $sens
#> [1] 0.99
#>
#> $mirt
#> [1] 0.01
#>
#> $spec
#> [1] 0.99
#>
#> $fart
#> [1] 0.01
#>
#> $ppod
#> [1] 0.9802
#>
#> $PPV
#> [1] 0.999898
#>
#> $FDR
#> [1] 0.00010202
#>
#> $NPV
#> [1] 0.5
#>
#> $FOR
#> [1] 0.5
#>
#> $acc
#> [1] 0.99
#>
#> $p_acc_hi
#> [1] 0.99
#>
#> $p_err_fa
#> [1] 0.01
#>
comp_prob(.99, sens = .90, spec = NA, fart = .10) # => ok: PPV = 0.9988789
#> $prev
#> [1] 0.99
#>
#> $sens
#> [1] 0.9
#>
#> $mirt
#> [1] 0.1
#>
#> $spec
#> [1] 0.9
#>
#> $fart
#> [1] 0.1
#>
#> $ppod
#> [1] 0.892
#>
#> $PPV
#> [1] 0.9988789
#>
#> $FDR
#> [1] 0.001121076
#>
#> $NPV
#> [1] 0.08333333
#>
#> $FOR
#> [1] 0.9166667
#>
#> $acc
#> [1] 0.9
#>
#> $p_acc_hi
#> [1] 0.99
#>
#> $p_err_fa
#> [1] 0.01
#>
# Watch out for extreme cases:
comp_prob(1, sens = 0, spec = 1) # => ok, but with warnings (as PPV & FDR are NaN)
#> Warning: Extreme case (prev = 1 & sens = 0):
#> N mi (FN) cases; 0 cond_false or dec_true cases; PPV = NaN.
#> Warning: PPV is NaN.
#> Warning: FDR is NaN.
#> Warning: Some derived prob values are peculiar. Check for extreme probabilities!
#> $prev
#> [1] 1
#>
#> $sens
#> [1] 0
#>
#> $mirt
#> [1] 1
#>
#> $spec
#> [1] 1
#>
#> $fart
#> [1] 0
#>
#> $ppod
#> [1] 0
#>
#> $PPV
#> [1] NaN
#>
#> $FDR
#> [1] NaN
#>
#> $NPV
#> [1] 0
#>
#> $FOR
#> [1] 1
#>
#> $acc
#> [1] 0
#>
#> $p_acc_hi
#> [1] NaN
#>
#> $p_err_fa
#> [1] 0
#>
comp_prob(1, sens = 0, spec = 0) # => ok, but with warnings (as PPV & FDR are NaN)
#> Warning: Extreme case (prev = 1 & sens = 0):
#> N mi (FN) cases; 0 cond_false or dec_true cases; PPV = NaN.
#> Warning: PPV is NaN.
#> Warning: FDR is NaN.
#> Warning: Some derived prob values are peculiar. Check for extreme probabilities!
#> $prev
#> [1] 1
#>
#> $sens
#> [1] 0
#>
#> $mirt
#> [1] 1
#>
#> $spec
#> [1] 0
#>
#> $fart
#> [1] 1
#>
#> $ppod
#> [1] 0
#>
#> $PPV
#> [1] NaN
#>
#> $FDR
#> [1] NaN
#>
#> $NPV
#> [1] 0
#>
#> $FOR
#> [1] 1
#>
#> $acc
#> [1] 0
#>
#> $p_acc_hi
#> [1] NaN
#>
#> $p_err_fa
#> [1] 0
#>
comp_prob(1, sens = 0, spec = NA, fart = 0) # => ok, but with warnings (as PPV & FDR are NaN)
#> Warning: Extreme case (prev = 1 & sens = 0):
#> N mi (FN) cases; 0 cond_false or dec_true cases; PPV = NaN.
#> Warning: PPV is NaN.
#> Warning: FDR is NaN.
#> Warning: Some derived prob values are peculiar. Check for extreme probabilities!
#> $prev
#> [1] 1
#>
#> $sens
#> [1] 0
#>
#> $mirt
#> [1] 1
#>
#> $spec
#> [1] 1
#>
#> $fart
#> [1] 0
#>
#> $ppod
#> [1] 0
#>
#> $PPV
#> [1] NaN
#>
#> $FDR
#> [1] NaN
#>
#> $NPV
#> [1] 0
#>
#> $FOR
#> [1] 1
#>
#> $acc
#> [1] 0
#>
#> $p_acc_hi
#> [1] NaN
#>
#> $p_err_fa
#> [1] 0
#>
comp_prob(1, sens = 0, spec = NA, fart = 1) # => ok, but with warnings (as PPV & FDR are NaN)
#> Warning: Extreme case (prev = 1 & sens = 0):
#> N mi (FN) cases; 0 cond_false or dec_true cases; PPV = NaN.
#> Warning: PPV is NaN.
#> Warning: FDR is NaN.
#> Warning: Some derived prob values are peculiar. Check for extreme probabilities!
#> $prev
#> [1] 1
#>
#> $sens
#> [1] 0
#>
#> $mirt
#> [1] 1
#>
#> $spec
#> [1] 0
#>
#> $fart
#> [1] 1
#>
#> $ppod
#> [1] 0
#>
#> $PPV
#> [1] NaN
#>
#> $FDR
#> [1] NaN
#>
#> $NPV
#> [1] 0
#>
#> $FOR
#> [1] 1
#>
#> $acc
#> [1] 0
#>
#> $p_acc_hi
#> [1] NaN
#>
#> $p_err_fa
#> [1] 0
#>
# Watch out for extreme cases:
comp_prob(1, sens = 0, spec = 1) # => ok, but with warnings (as PPV & FDR are NaN)
#> Warning: Extreme case (prev = 1 & sens = 0):
#> N mi (FN) cases; 0 cond_false or dec_true cases; PPV = NaN.
#> Warning: PPV is NaN.
#> Warning: FDR is NaN.
#> Warning: Some derived prob values are peculiar. Check for extreme probabilities!
#> $prev
#> [1] 1
#>
#> $sens
#> [1] 0
#>
#> $mirt
#> [1] 1
#>
#> $spec
#> [1] 1
#>
#> $fart
#> [1] 0
#>
#> $ppod
#> [1] 0
#>
#> $PPV
#> [1] NaN
#>
#> $FDR
#> [1] NaN
#>
#> $NPV
#> [1] 0
#>
#> $FOR
#> [1] 1
#>
#> $acc
#> [1] 0
#>
#> $p_acc_hi
#> [1] NaN
#>
#> $p_err_fa
#> [1] 0
#>
comp_prob(1, sens = 0, spec = 0) # => ok, but with warnings (as PPV & FDR are NaN)
#> Warning: Extreme case (prev = 1 & sens = 0):
#> N mi (FN) cases; 0 cond_false or dec_true cases; PPV = NaN.
#> Warning: PPV is NaN.
#> Warning: FDR is NaN.
#> Warning: Some derived prob values are peculiar. Check for extreme probabilities!
#> $prev
#> [1] 1
#>
#> $sens
#> [1] 0
#>
#> $mirt
#> [1] 1
#>
#> $spec
#> [1] 0
#>
#> $fart
#> [1] 1
#>
#> $ppod
#> [1] 0
#>
#> $PPV
#> [1] NaN
#>
#> $FDR
#> [1] NaN
#>
#> $NPV
#> [1] 0
#>
#> $FOR
#> [1] 1
#>
#> $acc
#> [1] 0
#>
#> $p_acc_hi
#> [1] NaN
#>
#> $p_err_fa
#> [1] 0
#>
comp_prob(1, sens = 0, spec = NA, fart = 0) # => ok, but with warnings (as PPV & FDR are NaN)
#> Warning: Extreme case (prev = 1 & sens = 0):
#> N mi (FN) cases; 0 cond_false or dec_true cases; PPV = NaN.
#> Warning: PPV is NaN.
#> Warning: FDR is NaN.
#> Warning: Some derived prob values are peculiar. Check for extreme probabilities!
#> $prev
#> [1] 1
#>
#> $sens
#> [1] 0
#>
#> $mirt
#> [1] 1
#>
#> $spec
#> [1] 1
#>
#> $fart
#> [1] 0
#>
#> $ppod
#> [1] 0
#>
#> $PPV
#> [1] NaN
#>
#> $FDR
#> [1] NaN
#>
#> $NPV
#> [1] 0
#>
#> $FOR
#> [1] 1
#>
#> $acc
#> [1] 0
#>
#> $p_acc_hi
#> [1] NaN
#>
#> $p_err_fa
#> [1] 0
#>
comp_prob(1, sens = 0, spec = NA, fart = 1) # => ok, but with warnings (as PPV & FDR are NaN)
#> Warning: Extreme case (prev = 1 & sens = 0):
#> N mi (FN) cases; 0 cond_false or dec_true cases; PPV = NaN.
#> Warning: PPV is NaN.
#> Warning: FDR is NaN.
#> Warning: Some derived prob values are peculiar. Check for extreme probabilities!
#> $prev
#> [1] 1
#>
#> $sens
#> [1] 0
#>
#> $mirt
#> [1] 1
#>
#> $spec
#> [1] 0
#>
#> $fart
#> [1] 1
#>
#> $ppod
#> [1] 0
#>
#> $PPV
#> [1] NaN
#>
#> $FDR
#> [1] NaN
#>
#> $NPV
#> [1] 0
#>
#> $FOR
#> [1] 1
#>
#> $acc
#> [1] 0
#>
#> $p_acc_hi
#> [1] NaN
#>
#> $p_err_fa
#> [1] 0
#>
comp_prob(1, sens = 1, spec = 0) # => ok, but with warnings (as NPV & FOR are NaN)
#> Warning: Extreme case (prev = 1 & sens = 1):
#> N hi (TP) cases; 0 cond_false or dec_false cases; NPV = NaN.
#> Warning: NPV is NaN.
#> Warning: FOR is NaN.
#> Warning: Some derived prob values are peculiar. Check for extreme probabilities!
#> $prev
#> [1] 1
#>
#> $sens
#> [1] 1
#>
#> $mirt
#> [1] 0
#>
#> $spec
#> [1] 0
#>
#> $fart
#> [1] 1
#>
#> $ppod
#> [1] 1
#>
#> $PPV
#> [1] 1
#>
#> $FDR
#> [1] 0
#>
#> $NPV
#> [1] NaN
#>
#> $FOR
#> [1] NaN
#>
#> $acc
#> [1] 1
#>
#> $p_acc_hi
#> [1] 1
#>
#> $p_err_fa
#> [1] NaN
#>
comp_prob(1, sens = 1, spec = 1) # => ok, but with warnings (as NPV & FOR are NaN)
#> Warning: Extreme case (prev = 1 & sens = 1):
#> N hi (TP) cases; 0 cond_false or dec_false cases; NPV = NaN.
#> Warning: NPV is NaN.
#> Warning: FOR is NaN.
#> Warning: Some derived prob values are peculiar. Check for extreme probabilities!
#> $prev
#> [1] 1
#>
#> $sens
#> [1] 1
#>
#> $mirt
#> [1] 0
#>
#> $spec
#> [1] 1
#>
#> $fart
#> [1] 0
#>
#> $ppod
#> [1] 1
#>
#> $PPV
#> [1] 1
#>
#> $FDR
#> [1] 0
#>
#> $NPV
#> [1] NaN
#>
#> $FOR
#> [1] NaN
#>
#> $acc
#> [1] 1
#>
#> $p_acc_hi
#> [1] 1
#>
#> $p_err_fa
#> [1] NaN
#>
comp_prob(1, sens = 1, spec = NA, fart = 0) # => ok, but with warnings (as NPV & FOR are NaN)
#> Warning: Extreme case (prev = 1 & sens = 1):
#> N hi (TP) cases; 0 cond_false or dec_false cases; NPV = NaN.
#> Warning: NPV is NaN.
#> Warning: FOR is NaN.
#> Warning: Some derived prob values are peculiar. Check for extreme probabilities!
#> $prev
#> [1] 1
#>
#> $sens
#> [1] 1
#>
#> $mirt
#> [1] 0
#>
#> $spec
#> [1] 1
#>
#> $fart
#> [1] 0
#>
#> $ppod
#> [1] 1
#>
#> $PPV
#> [1] 1
#>
#> $FDR
#> [1] 0
#>
#> $NPV
#> [1] NaN
#>
#> $FOR
#> [1] NaN
#>
#> $acc
#> [1] 1
#>
#> $p_acc_hi
#> [1] 1
#>
#> $p_err_fa
#> [1] NaN
#>
comp_prob(1, sens = 1, spec = NA, fart = 1) # => ok, but with warnings (as NPV & FOR are NaN)
#> Warning: Extreme case (prev = 1 & sens = 1):
#> N hi (TP) cases; 0 cond_false or dec_false cases; NPV = NaN.
#> Warning: NPV is NaN.
#> Warning: FOR is NaN.
#> Warning: Some derived prob values are peculiar. Check for extreme probabilities!
#> $prev
#> [1] 1
#>
#> $sens
#> [1] 1
#>
#> $mirt
#> [1] 0
#>
#> $spec
#> [1] 0
#>
#> $fart
#> [1] 1
#>
#> $ppod
#> [1] 1
#>
#> $PPV
#> [1] 1
#>
#> $FDR
#> [1] 0
#>
#> $NPV
#> [1] NaN
#>
#> $FOR
#> [1] NaN
#>
#> $acc
#> [1] 1
#>
#> $p_acc_hi
#> [1] 1
#>
#> $p_err_fa
#> [1] NaN
#>
# Ways to fail:
comp_prob(NA, 1, 1, NA) # => only warning: invalid set (prev not numeric)
#> Warning: Invalid probabilities. Please enter a valid set of essential probabilities.
comp_prob(8, 1, 1, NA) # => only warning: prev no probability
#> Warning: Invalid probabilities. Please enter a valid set of essential probabilities.
comp_prob(1, 8, 1, NA) # => only warning: sens no probability
#> Warning: Invalid probabilities. Please enter a valid set of essential probabilities.
comp_prob(1, 1, 1, 1) # => only warning: is_complement not in tolerated range
#> Warning: Probabilities (p1 and p2) are not complements (in tolerated range).
#> Warning: Invalid probabilities. Please enter a valid set of essential probabilities.