Man pages for oizin/funnelplot
Create Funnel Plots
| accuracy | accuracy |
| adjParams | Casemix adjustment |
| auc_roc | Area under the receiver operating characteristic curve |
| bonferroni | Bonferroni multiplicity adjustment. |
| calcExpected | Casemix adjustment |
| check_distTarget | Check arguments on distTarget |
| check_formula | Check the input to funnel |
| check_pointTarget | Check arguments on pointTarget |
| classify | classify a probability |
| confusion | labels data like a confusion matrix |
| contAdjustBin | Continuity adjusted binomial limits |
| dispersion | Dispersion parameters |
| distTarget | Target is a distribution |
| eg_sample_func | Example sampling function for simulate |
| err | error rate |
| evalCasemixAdj | Evaluate ability of casemix adjustment variables to predict... |
| example_data | Example dataset for the funnelplot pacakge |
| fdr | False discovery rate multiplicity adjustment |
| fpr | fpr |
| funnelModel | Table of results for risk adjusted funnel plots. |
| generate_example | Simulate data for a funnel plot |
| getFunnelFormula | Edit funnel plot formula |
| groupOutcomes | Calculate summary values per cluster |
| normHypTest | Normal assuming hypothesis test on grouped data |
| outliers | List institutional outliers |
| plot.funnelRes | Graph funnel plot |
| plotLimits | helper function for plotting the funnel plots |
| pointLimits | Calculate control limits |
| pointTarget | Target is a point |
| ppv | precision, positive predictive value |
| pr | precision recall curves |
| print.funnelRes | print function |
| randomEffectLimits | Calculate control limits |
| roc | Receiver operating characteristic curve |
| sample_means | Sample means |
| sample_nobs | Sample a certain number of observations |
| sp | specificity |
| summary.funnelRes | Cluster performance summary |
| theme_funnel | A ggtheme |
| tpr | recall, sensitivity, true positive rate |
