| Figure 2.1 |
Histogram of difference in two ages, stratified by imputation type |
| Figure 2.2 |
Missing data patterns in d |
| Figure 2.3 |
Plot of the degree of symmetry of the distribution of a variable (value of 1.0 is most symmetric) vs. the number of distinct values of the variable. Hover over a point to see the variable name and detailed characteristics. |
| Figure 2.4 |
Categorical variable proportions for titanic5 |
| Figure 2.5 |
Continuous variable spike histograms for titanic5 |
| Figure 2.6 |
Dot plot of proportion of males by class using Hmisc::summaryM |
| Figure 2.7 |
Extended box plots showing age and ticket price distributions by sex |
| Figure 2.8 |
Extended box plots of age and price by class |
| Figure 2.9 |
Scatter plot of ticket price vs. age |
| Figure 2.10 |
Moving proportion survived vs. price by class |
| Figure 2.11 |
Moving proportion survived plus LR and loess estimates |
| Figure 2.12 |
Nonparametric smoother for survival vs. age by class and sex |
| Figure 6.1 |
Missing data patterns in support |
| Figure 8.1 |
Consort diagram produced with consort_plot |
| Figure 8.2 |
Consort diagram using component functions |
| Figure 8.3 |
Consort diagram produced by mermaid |
| Figure 8.4 |
Consort diagram produced with mermaid with individual exclusions linked to the overall exclusions node, and with a tooltip to show more detail |
| Figure 8.5 |
Consort diagram produced with graphviz with detailed exclusion frequencies in a separate node |
| Figure 8.6 |
Flowchart of sequential exclusion of observations due to missing values |
| ?fig-overview1 |
Plot of the degree of symmetry of the distribution of a variable (value of 1.0 is most symmetric) vs. the number of distinct values of the variable. Hover over a point to see the variable name and detailed characteristics. |
| Figure 9.1 |
Regular plot(describe) output |
| ?fig-pldesc1 |
plotly plot(describe) output |
| ?fig-summaryM3 |
summaryM plots |
| Figure 9.2 |
Spike histograms of heart rate stratified by ECG category |
| Figure 9.5 |
Representative curves determined by curveRep stratified by per-subject sample size ranges |
| ?fig-descript-multevent |
Multi-event chart for 4 patients |
| Figure 9.8 |
State transition proportions |
| Figure 9.9 |
State occupancy proportions by time and male/female |
| ?fig-aeplot |
Proportion of adverse events by Treatment |
| Figure 9.10 |
Event chart |
| Figure 9.11 |
Spearman rank correlation matrix. Positive correlations are blue and negative are red. |
| Figure 18.1 |
Simulation of maximum absolute correlation coefficient |
| Figure 18.2 |
Average of maximum absolute correlation coefficients |
| Figure 15.1 |
Nonparametric smooth estimated relationships between several continuous variables and probability of hospital death |
| Figure 15.2 |
Prototype extended box plot |
| Figure 15.3 |
bpplotM extended box plot |
| Figure 15.4 |
summaryM plotly graphic with interactive extended box plots |
| Figure 15.5 |
ggfreqScatter plot showing all raw data for two continuous variables with only slight binning |
| Figure 15.6 |
movStats moving estimates of mean and quantiles |
| Figure 15.7 |
Moving mean and quantile estimates of effect of age with interquartile bands |
| Figure 15.8 |
Moving estimates of WBC vs. hospital mortality |
| Figure 15.9 |
Moving nonparametric and flexible parametric estimates of mortality |
| Figure 15.10 |
1-year mortality estimates stratified by disease group |
| Figure 15.11 |
Stratified moving Kaplan-Meier and HARE estimates varying age |
| Figure 15.12 |
Moving estimates of effect of age on glycohemoglobin stratified by race/ethnicity |
| Figure 15.13 |
Parametric spline estimates of age vs. glycohemoglobin |
| Figure 15.14 |
Smooth age effects on three quartiles of HbA\(_{1c}\) |
| Figure 15.15 |
Moving Kaplan-Meier and HARE esetimates for several continuous covariates |
| Figure 15.16 |
Kaplan-Meier estimates of 1y and 2y incidence stratified separately by a series of discrete predictorsw |
| Figure 15.17 |
Kaplan-Meier estimates of 1y and 2y incidence with each predictor in its own tab |
| Figure 15.18 |
Interactive survival curves with half-width confidence bands |
| Figure 15.19 |
Spearman correlations between pairwise clinical chemistry/hematology variable correlations and time |
| Figure 15.20 |
Graphical representations of a fitted binary logistic model |