splineplot 0.3.0

New Features

• Survey-weighted model support: Added support for svyglm and svycoxph models from the survey package
  • svyglm: Survey-weighted GLM models (logistic, Poisson, Gaussian) with ns() or bs() splines
  • svycoxph: Survey-weighted Cox proportional hazards models with ns() or bs() splines
  • Uses spline-coefficient extraction approach to avoid model.matrix contrasts issues with survey objects
  • Supports both single spline terms and interaction terms (ns(x) * group)
  • Survey-adjusted variance-covariance matrix (sandwich estimator) is properly used for confidence intervals
• Moved splines from Suggests to Imports for direct basis construction in survey model path

splineplot 0.2.2

Bug Fixes

• Fixed error when plotting Cox/GLM models with categorical covariates
  • extract_spline_data() now properly preserves factor levels when creating prediction data
  • Previously caused “contrasts can be applied only to factors with 2 or more levels” error
  • Affects models like coxph(Surv(time, status) ~ ns(x, df=4) + sex + age_group, data=dat)

splineplot 0.2.1

Bug Fixes

• Fixed lines being drawn outside Y-axis limits when confidence intervals exceed ylim range
  • Lines now properly stop when they go out of bounds instead of extending beyond axis limits
  • Each line (main curve, lower CI, upper CI) is handled independently
  • If lower CI goes below ylim, only that line is clipped while upper CI continues if still in range
  • Ensures clean, professional-looking plots that respect specified axis boundaries

splineplot 0.2.0

Major Improvements

• Y-axis scaling: Implemented proper ratio scale display for HR/OR/RR when log_scale=FALSE
  • Shows actual ratio values (e.g., 0.5, 1, 2) instead of log values
  • Automatically selects appropriate breaks based on data range
  • Removes trailing zeros from labels (1.50 → 1.5)
• X-axis improvements:
  • Fixed X-axis tick visibility and direction (now properly pointing downward)
  • Adjusted plot limits to ensure ticks are always visible
• Histogram alignment: Base of histogram now correctly aligns with secondary Y-axis 0%
• Internal refactoring: Simplified data handling by always using log scale internally for ratio metrics
  • log_scale parameter now only affects Y-axis label display
  • More consistent and predictable behavior

Bug Fixes

• Fixed missing Y-axis labels in GAM interaction plots
• Corrected reference line position (always at y=0 for log scale, which represents ratio=1)
• Fixed ylabel column missing in extract_spline_interaction() output

splineplot 0.1.1

Bug Fixes

• Fixed Y-axis tick marks display issue in interaction plots
• Fixed tick marks protruding from axes when histogram is shown
• Corrected secondary Y-axis scale for “Percent of Population” in interaction plots
• Fixed X-axis positioning with floating axis for histogram display
• Improved axis tick alignment for both single and interaction plots

Documentation

• Updated GAM survival examples to use recommended weights parameter format
• Removed unnecessary logo reference from README
• Clarified that GAM Cox models should use time ~ s(predictor), weights = status format

splineplot 0.1.0

Initial Release

Major Features

• Unified interface for visualizing spline effects from GAM and GLM models
• Support for multiple model types:
  • GAM models from mgcv package with s(), te(), ti() smooth terms
  • GLM/LM models with ns() and bs() splines from splines package
  • Cox proportional hazards models from survival package
• Automatic detection of:
  • Model type and family
  • Spline terms
  • Interaction variables
• Support for various outcome types:
  • Hazard Ratios (HR) for Cox models
  • Odds Ratios (OR) for logistic models
  • Rate Ratios (RR) for Poisson models
  • Effects for linear/Gaussian models

Visualization Features

• Publication-ready ggplot2 output
• Customizable confidence intervals:
  • Dotted lines (default)
  • Ribbon/shaded style
• Built-in histogram showing data distribution
• Reference point marking with automatic SE = 0
• Support for interaction terms with by-variable
• Log scale option for ratio outcomes
• Customizable axis labels and limits

Technical Features

• Automatic handling of different spline basis functions
• Proper reference value centering with SE = 0
• Support for both Surv() and weights methods in GAM Cox models
• Limited support for pspline() in Cox models

Known Limitations

• pspline() in Cox models has limited support due to internal structure
• Recommend using ns() or bs() with Cox models for optimal results