prob is a list of named numeric variables containing 3 essential (1 non-conditional prev and 2 conditional sens and spec) probabilities and 8 derived (ppod and acc, as well as 6 conditional) probabilities:

prob

Format

An object of class list of length 13.

Details

prob currently contains the following probabilities:

  1. the condition's prevalence prev (i.e., the probability of the condition being TRUE): prev = cond_true/N.

  2. the decision's sensitivity sens (i.e., the conditional probability of a positive decision provided that the condition is TRUE).

  3. the decision's miss rate mirt (i.e., the conditional probability of a negative decision provided that the condition is TRUE).

  4. the decision's specificity spec (i.e., the conditional probability of a negative decision provided that the condition is FALSE).

  5. the decision's false alarm rate fart (i.e., the conditional probability of a positive decision provided that the condition is FALSE).

  6. the proportion (baseline probability or rate) of the decision being positive ppod (but not necessarily true): ppod = dec_pos/N.

  7. the decision's positive predictive value PPV (i.e., the conditional probability of the condition being TRUE provided that the decision is positive).

  8. the decision's false detection (or false discovery) rate FDR (i.e., the conditional probability of the condition being FALSE provided that the decision is positive).

  9. the decision's negative predictive value NPV (i.e., the conditional probability of the condition being FALSE provided that the decision is negative).

  10. the decision's false omission rate FOR (i.e., the conditional probability of the condition being TRUE provided that the decision is negative).

  11. the accuracy acc (i.e., probability of correct decisions dec_cor or correspondence of decisions to conditions).

  12. the conditional probability p_acc_hi (i.e., the probability of hi given that the decision is correct dec_cor).

  13. the conditional probability p_err_fa (i.e., the probability of fa given that the decision is erroneous dec_err).

These probabilities are computed from basic probabilities (contained in num) and computed by using comp_prob.

The list prob is the probability counterpart to the list containing frequency information freq.

Note that inputs of extreme probabilities (of 0 or 1) may yield unexpected values (e.g., an NPV value of NaN when is_extreme_prob_set evaluates to TRUE).

Key relationships between frequencies and probabilities (see documentation of comp_freq or comp_prob for details):

  • Three perspectives on a population:

    by condition / by decision / by accuracy.

  • Defining probabilities in terms of frequencies:

    Probabilities can be computed as ratios between frequencies, but beware of rounding issues.

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).

Visualizations of current probability information are provided by plot_area, plot_prism, and plot_curve.

See also

num contains basic numeric parameters; init_num initializes basic numeric parameters; txt contains current text information; init_txt initializes text information; pal contains current color information; init_pal initializes color information; freq contains current frequency information; comp_freq computes current frequency information; prob contains current probability information; comp_prob computes current probability information; accu contains current accuracy information.

Other lists containing current scenario information: accu, freq, num, pal_bw, pal_kn, pal_mbw, pal_mod, pal_org, pal_rgb, pal_vir, pal, txt_TF, txt_org, txt

Examples

prob <- comp_prob() # => initialize prob to default parameters prob # => show current values
#> $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(prob) # => 13
#> [1] 13