Package: hvtiPlotR 2.8.16

The Composition Pattern | Themes | Manuscript | Poster | Light PowerPoint | Dark PowerPoint | One decorator for a whole deck | Naming the series without a legend | Designing the slide around the figure | Color Scales | Manual colors | ColorBrewer palettes | Suppressing legends | Labels and Annotations | labs() | annotate() | coord_cartesian() | Saving Figures | Manuscript PDF | Poster PDF | PowerPoint slides | Single slide | Multiple slides from a list | Fixed panel placement across slides | Multi-panel PDF (EDA batch output) | Legend Positioning | Inside the panel | Outside the panel (explicit sides) | Suppress all legends | Legend text and key size | Theme Overrides | Axis text size | Removing minor grid lines | Rotating x-axis labels | Adding a plot title and subtitle | Expanding plot margins | Multi-panel Figures with patchwork | Side-by-side plots | Controlling relative widths and heights | Stacking a plot above a risk table | Shared axis labels and panel tags | Saving a patchwork composite

Template Reference Map | Mirrored Propensity Score Histogram | Binary-match mode (SAVR vs. TF-TAVR) | Bare plot | Adding scales, labels, and theme | Weighted IPTW mode (Limited vs. Extended) | Bare plot | Adding scales, labels, and theme | Stacked Histogram | Count histogram | Proportion (fill) histogram | Saving | Goodness-of-Follow-Up Plot | Sample data | Death follow-up plot | Adding scales, labels, and annotations | Non-fatal event panel | Several panels over one window | Role colors across panels | Covariate Balance Plot | Adding color, shape, and axis scales | Adding directional annotations and theme | Controlling covariate order | Kaplan-Meier Survival Curve | Survival curve (PLOTS=1) | Numbers at risk and report table | Stratified analysis | Survival curve with a numbers-at-risk table | Cumulative hazard (PLOTC=1) | Log-log survival plot (Weibull/PH check) | Hazard rate (PLOTH=1) | Integrated survivorship / restricted mean survival (PLOTL=1) | RMST Contrast and Curves | Differences by estimator | Weighted curves with the RMST area | Correlation Matrix | EDA Barplots and Scatterplots | Binary categorical: count barplot | Binary categorical: percentage barplot | Ordinal and multi-level categorical | Character categorical | Continuous: scatter + LOESS | Variable selection and labels (varnames template pattern) | Several variables to a page | Saving EDA plots | Alluvial (Sankey) Plot | Fill flows by pre-operative grade | Two-axis before / after comparison | Cluster Stability Sankey Plot | Default plot (K = 2 to 9) | Custom color palette | Subset of K values | CONSORT Patient Flow Diagram | Building a tracker from your own data | The diagram | Auditing the cohort | Hazard Plot | Survival curve with KM overlay | Hazard rate curve | Cumulative hazard | Stratified by group | Life-table overlay | The hv_hazard() object interface | Survival Difference (Life-Gained) Plot | Survival difference curve | Multiple comparisons | The hv_survival_difference() object interface | Number Needed to Treat (NNT) Plot | NNT curve | Absolute risk reduction | The hv_nnt() object interface | Temporal Trend Plot | Single variable: cases/year | Single variable: age | Multiple groups with scale_color_brewer | Median summary + manual colors (NYHA style) | With confidence ribbon | Binary % outcomes (tp.lp.trends.sas) | Age as x-axis (tp.lp.trends.age.sas) | Polytomous groups: repair types (tp.lp.trends.polytomous.sas) | LV mass index (tp.dp.trends.R, plot2) | Case volume / total surgeries per year (tp.dp.trends.R, plot4) | Annotated trend: hospital LOS (tp.dp.trends.R, plot5) | Spaghetti / Profile Plot | Unstratified: AV mean gradient, full range (plot_1) | Unstratified: zoomed y-axis (plot_3) | Stratified by sex: AV mean gradient (plot_2 / plot_4) | AV area y-scale (plot_5 / plot_6) | DVI y-scale (plot_7 / plot_8) | Ordinal y-axis: MV regurgitation grade (plot_9) | With LOESS smooth overlay | Nonparametric Temporal Trend Curve | Single average curve with 68 % CI ribbon | Two-group comparison (analogous to tp.np.avpkgrad_ozak_ind_mtwt.sas) | Nonparametric Ordinal Outcome Curve | Grade probability curves with data summary points | Combined mild + moderate (p34 = p3 + p4 pattern) | Longitudinal Participation Counts | Bar chart | Numeric table panel | Two-panel layout with patchwork | Saving the combined figure | UpSet Plot | Default plot | Custom intersection bar color | Color bars by era | Venn diagram (2-3 sets) | Draft Footnotes | Draft annotation pattern | Custom analyst tag | Saving without the footnote

Overview | Key concepts for SAS users | Template lookup table | Nonparametric temporal trends (tp.np.*) | SAS column name mapping | Average curve: binary outcome | Continuous outcome | Multi-group comparison | Phase decomposition | Covariate on the x-axis | Ordinal outcomes | Ordinal multi-scenario comparison | Ordinal phase independence | Ordinal phases | Survival analysis (tp.ac.dead.*, tp.cp.dead.*) | SAS → R argument mapping | Goodness of follow-up (tp.dp.gfup.R) | Covariate balance (tp.lp.propen.cov_balance.R) | Alluvial flow (tp.dp.female_bicus_preAR_sankey.R) | Cluster stability Sankey (PAM analysis) | SAS/R workflow → R equivalent | UpSet plot (tp.complexUpset.R) | Spaghetti / individual trajectories (tp.dp.spaghetti.echo.R) | Unstratified: AV mean gradient full range (plot_1) | Unstratified: zoomed y-axis (plot_3) | Stratified by sex (plot_2 / plot_4) | AV area y-scale (plot_5 / plot_6) | DVI y-scale (plot_7 / plot_8) | Ordinal y-axis: MV regurgitation grade (plot_9) | Correlation matrix (descriptive/dc.tables.ods.sas) | Trends over time (tp.*.trends.*) | tp.rp.trends.sas: cases/year and age (1968–2000 by 4) | tp.lp.trends.sas: binary % outcomes (1970–2000 by 10, y 0–100 by 10) | tp.lp.trends.age.sas: age on x-axis (25–85 by 10, y 0–100 by 20) | tp.lp.trends.polytomous.sas: repair types (1990–1999 by 1, y 0–100 by 10) | tp.dp.trends.R: LV mass index (1995–2015 by 5, y 0–200 by 50) | tp.dp.trends.R: hospital LOS with annotation (1985–2015 by 5, y 0–20 by 5) | Longitudinal patient counts (tp.dp.longitudinal_patients_measures.R) | EDA postage stamps (tp.dp.EDA_barplots_scatterplots*.R) | Mirror histogram (propensity score) | Binary-match mode (tp.lp.mirror-histogram_SAVR-TF-TAVR.R) | Weighted IPTW mode (tp.lp.mirror_histo_before_after_wt.R) | Stacked histogram | Using themes | Saving figures | PowerPoint | PDF / TIFF for journals | Parametric hazard/survival (tp.hs.*) | Parametric survival with KM overlay | Stratified by covariate | Conditional survival after hospital discharge | US life-table overlay | Treatment benefit distribution | Adding new ports | Session info

Abstract | About this document | Introduction | The plot.sas macro | SAS → R Quick Reference | Structure and output | Axis labels and scales | Tuple statements: points and error bars | Tuple statements: lines and ribbons | Symbols and colors reference | Device and theme mapping | Generating ggplot2 graphics | Importing the data | Option 1: SAS xport file (recommended when you have SAS access) | Option 2: CSV export (when SAS is not available) | Using the bundled example data | Initialize the figure | Labels | Scales | Points | Error Bars | Lines | Line types | Shapes | Colors | Global Figure Commands | PowerPoint Figures | Themes and Decoration | Saving publication graphics | Manuscript graphics | PowerPoint graphics | Graphics rules to live by | Manuscript figures | PowerPoint figures | Color | What not to include | Conclusions | References | Affiliation:

Development environment setup | Prerequisites | Installing development dependencies | The development workflow loop | Track A: Porting a SAS template | Step 1: Understand the SAS template output | Step 2: Create the R source file | The constructor | The print and plot methods | Step 3: Add a sample-data generator | Step 4: Write roxygen documentation | Step 5: Register in _pkgdown.yml | Step 6: Add a worked example to the plot-functions vignette | Step 7: Add a row to the SAS migration guide | Step 8: Write tests | Step 9: Update NEWS.md | Step 10: Final checklist before opening a PR | Track B: Package infrastructure | Package structure overview | Adding a dependency | Code style and conventions | File and function naming | The bare-ggplot pattern | Tidy evaluation | Testing | Test file layout | Snapshot tests | Running checks | What R CMD CHECK validates | Vignette conventions | Releasing a new version | Session info