Full lists of arguments

cifcurve()

• formula A model formula specifying the time-to-event outcome on the left-hand side (typically Event(time, status) or survival::Surv(time, status)) and, optionally, a stratification variable on the right-hand side. Unlike cifplot(), this function does not accept a fitted survfit object.
• data A data frame containing variables in formula.
• weights Optional name of the weight variable in data. Weights must be nonnegative.
• subset.condition Optional character expression to subset data before analysis.
• na.action A function specifying the action to take on missing values (default na.omit).
• outcome.type Character string specifying the type of time-to-event outcome. One of "survival" (Kaplan-Meier) or "competing-risk" (Aalen-Johansen). If NULL (default), the function automatically infers the outcome type from the data: if the event variable has more than two unique levels, "competing-risk" is assumed; otherwise, "survival" is used. You can also use abbreviations such as "S" or "C". Mixed or ambiguous inputs (e.g., c("S", "C")) trigger automatic detection based on the event coding.
• code.event1 Integer code of the event of interest (default 1).
• code.event2 Integer code of the competing event (default 2).
• code.censoring Integer code of censoring (default 0).
• error Character string specifying the method for SEs and CIs used internally. For "survival" without weights, choose one of "greenwood" (default), "tsiatis", or "if". For "competing-risk" without weights, choose one of "delta" (default), "aalen", or "if". SEs and CIs based on influence functions ("if") is recommended for weighted analysis.
• conf.type Character specifying the method of transformation for CIs used internally (default "arcsine-square root").
• conf.int Numeric two-sided level of CIs (default 0.95).
• return_if Logical. When TRUE and engine = "calculateAJ_Rcpp", the influence function is also computed and returned (default FALSE).
• report.survfit.std.err Logical. If TRUE, report SE on the log-survival scale (survfit’s convention). Otherwise SE is on the probability scale.
• engine Character. One of "auto", "calculateKM", or "calculateAJ_Rcpp" (default "calculateAJ_Rcpp").
• prob.bound Numeric lower bound used to internally truncate probabilities away from 0 and 1 (default 1e-7).

cifplot()

• formula_or_fit A model formula or a survfit object. Note: When a formula is supplied, the left-hand side must be Event(time, status) or survival::Surv(time, status).
• data A data frame containing variables in formula.
• weights Optional name of the weight variable in data. Weights must be nonnegative.
• subset.condition Optional character expression to subset data before analysis.
• na.action A function specifying the action to take on missing values (default na.omit).
• outcome.type Character string specifying the type of time-to-event outcome. One of "survival" (Kaplan-Meier) or "competing-risk" (Aalen-Johansen). If NULL (default), the function automatically infers the outcome type from the data: if the event variable has more than two unique levels, "competing-risk" is assumed; otherwise, "survival" is used. You can also use abbreviations such as "S" or "C". Mixed or ambiguous inputs (e.g., c("S", "C")) trigger automatic detection based on the event coding.
• code.event1 Integer code of the event of interest (default 1).
• code.event2 Integer code of the competing event (default 2).
• code.censoring Integer code of censoring (default 0).
• error Character string specifying the method for SEs and CIs used internally. For "survival" without weights, choose one of "greenwood" (default), "tsiatis", or "if". For "competing-risk" without weights, choose one of "delta" (default), "aalen", or "if". SEs and CIs based on influence functions ("if") is recommended for weighted analysis.
• conf.type Character specifying the method of transformation for CIs used internally (default "arcsine-square root").
• conf.int Numeric two-sided level of CIs (default 0.95).
• type.y Character string specifying the y-scale. For survival/CIF curves, "surv" implies survival probabilities and "risk" implies CIF (1-survival in simple survival settings). Specify "cumhaz" to plot cumulative hazard or "cloglog" to generate a complementary log-log plot. If NULL, a default is chosen from outcome.type or the survfit object.
• label.x Character x-axis labels (default "Time").
• label.y Character y-axis label (default is chosen automatically from outcome.type and type.y, e.g. “Survival”, “Cumulative incidence” or “Cumulative hazard”).
• label.strata Character vector of labels for strata.
• order.strata Optional ordering of strata levels. When panel.per.variable = TRUE, supply a named list list(var = c("L1","L2",...)) for each RHS variable; unmatched levels are dropped. When panel.per.variable = FALSE, supply a character vector c("L1","L2",...) that specifies the display order (legend/risktable) of the single stratification factor. Levels not listed are dropped. If label.strata is a named vector, its names must match the (re-ordered) levels.
• limits.x Numeric length-2 vectors for axis limits. If NULL it is internally set to c(0,max(out_read_surv$t)).
• limits.y Numeric length-2 vectors for axis limits. If NULL it is internally set to c(0,1).
• breaks.x Numeric vectors for axis breaks (default NULL).
• breaks.y Numeric vectors for axis breaks (default NULL).
• use.coord.cartesian Logical; if TRUE, uses ggplot2::coord_cartesian() for zooming instead of changing the scale limits (default FALSE).
• add.conf Logical add add_confidence_interval() to plot. It calls geom_ribbon() (default TRUE).
• add.risktable Logical add add_risktable(risktable_stats="n.risk") to plot (default TRUE).
• add.estimate.table Logical add add_risktable(risktable_stats="estimate (conf.low, conf.high)") to plot (default FALSE).
• symbol.risk.table Character specifying the symbol used in the risk table to denote strata: "square", "circle", or "triangle" (default "square").
• font.size.risk.table Numeric font size for texts in risk / estimate tables (default 3).
• add.censor.mark Logical add add_censor_mark() to plot. It calls geom_point() (default TRUE).
• shape.censor.mark Integer point shape for censor marks (default 3).
• size.censor.mark Numeric point size for censor marks (default 2).
• add.competing.risk.mark Logical add time marks to describe event2 specified by Event(), usually the competing events. It calls geom_point() (default TRUE).
• competing.risk.time Named list of numeric vectors (names must be mapped to strata labels).
• shape.competing.risk.mark Integer point shape for competing-risk marks (default 16).
• size.competing.risk.mark Numeric point size for competing-risk marks (default 2).
• add.intercurrent.event.mark Logical overlay user-specified time marks per strata calls geom_point() (default TRUE).
• intercurrent.event.time Named list of numeric vectors (names must be mapped to strata labels).
• shape.intercurrent.event.mark Integer point shape for intercurrent-event marks (default 1).
• size.intercurrent.event.mark Numeric point size for intercurrent-event marks (default 2).
• add.quantile Logical add add_quantile() to plot. It calls geom_segment() (default TRUE).
• level.quantile Numeric quantile level for add_quantile() (default 0.5).
• panel.per.event Logical. Explicit panel mode. If TRUE and outcome.type == "competing-risk", cifplot() internally calls cifpanel() to display two event-specific CIFs side-by-side (event 1 and event 2) using reversed code.events. Ignored for non-competing-risk outcomes.
• panel.censoring Logical. Explicit panel mode. If TRUE and outcome.type == "survival", cifplot() internally calls cifpanel() to display KM-type curves for (event, censor) and (censor, event) so that censoring patterns can be inspected.
• panel.per.variable Logical. Explicit panel mode. If TRUE and the right-hand side of the formula has multiple covariates (e.g. ~ a + b + c), the function produces a panel where each variable in RHS is used once as the stratification factor.
• panel.mode Character specifying Automatic panel mode. If "auto" and none of panel.per.variable, panel.per.event, panel.censoring has been set to TRUE, the function chooses a suitable panel mode automatically: (i) if the formula RHS has 2+ variables, it behaves like panel.per.variable = TRUE; (ii) otherwise, if outcome.type == "competing-risk", it behaves like panel.per.event = TRUE; (iii) otherwise, if outcome.type == "survival", it behaves like panel.censoring = TRUE. If a panel mode is explicitly specified, panel.mode is ignored.
• rows.columns.panel Optional integer vector c(nrow, ncol) controlling the panel layout. If NULL, an automatic layout is used.
• style Character plot theme controls (default "classsic").
• palette Optional character vector specify color palette, e.g. palette=c("blue", "cyan", "navy", "green") (default NULL).
• linewidth Optional numeric specifying the line width of curve (default 0.8).
• linetype Optional logical using different line types of curve (default \code{FALSE`).
• font.family Character plot theme controls (e.g. "sans", "serif", and "mono". default "sans").
• font.size Integer plot theme controls (default 12).
• legend.position Character specify position of legend: "top", "right", "bottom", "left", or "none" (default "top").
• filename.ggsave Character save the ggsurvfit plot with the path and name specified.
• width.ggsave Numeric specify width of the ggsurvfit plot.
• height.ggsave Numeric specify height of the ggsurvfit plot.
• dpi.ggsave Numeric specify dpi of the ggsurvfit plot.

cifpanel()

• plots Optional list of existing ggplot objects to be arranged into a panel. When plots is supplied, no new models are fitted; the plots are used as-is.

• formula A model formula specifying the time-to-event outcome on the left-hand side (typically Event(time, status) or survival::Surv(time, status)) and, optionally, a stratification variable on the right-hand side. Unlike cifplot(), this function does not accept a fitted survfit object.

• formulas A list of formulas (one per panel). If provided, overrides formula.

• data A data frame containing variables in formula.

• weights Optional name of the weight variable in data. Weights must be nonnegative.

• subset.condition Optional character expression to subset data before analysis.

• na.action A function specifying the action to take on missing values (default na.omit).

• outcome.type Character string specifying the type of time-to-event outcome. One of "survival" (Kaplan-Meier) or "competing-risk" (Aalen-Johansen). If NULL (default), the function automatically infers the outcome type from the data: if the event variable has more than two unique levels, "competing-risk" is assumed; otherwise, "survival" is used. You can also use abbreviations such as "S" or "C". Mixed or ambiguous inputs (e.g., c("S", "C")) trigger automatic detection based on the event coding.

• code.event1 Integer code of the event of interest (default 1).

• code.event2 Integer code of the competing event (default 2).

• code.censoring Integer code of censoring (default 0).

• code.events Optional numeric length-3 vector c(event1, event2, censoring). When supplied, it overrides code.event1, code.event2, and code.censoring (primarily used when cifpanel() is called or when panel.per.event = TRUE).

• error Character string specifying the method for SEs and CIs used internally. For "survival" without weights, choose one of "greenwood" (default), "tsiatis", or "if". For "competing-risk" without weights, choose one of "delta" (default), "aalen", or "if". SEs and CIs based on influence functions ("if") is recommended for weighted analysis.

• conf.type Character specifying the method of transformation for CIs used internally (default "arcsine-square root").

• conf.int Numeric two-sided level of CIs (default 0.95).

• type.y Character string specifying the y-scale. For survival/CIF curves, "surv" implies survival probabilities and "risk" implies CIF (1-survival in simple survival settings). Specify "cumhaz" to plot cumulative hazard or "cloglog" to generate a complementary log-log plot. If NULL, a default is chosen from outcome.type or the survfit object.

• label.x, label.y Optional vectors/lists of axis labels per panel.

• label.strata Optional list of character vectors for legend labels per panel (passed to cifplot()).

• order.strata Optional list of character vectors for ordering labels per panel (passed to cifplot()).

• limits.x, limits.y Optional vectors/lists of numeric length-2 axis limits per panel.

• breaks.x, breaks.y Optional vectors/lists of axis breaks per panel (forwarded to breaks.x / breaks.y in cifplot()).

• add.conf, add.censor.mark, add.competing.risk.mark, add.intercurrent.event.mark, add.quantile Optional logical vectors/lists per panel to toggle features in cifplot(). If NULL, sensible defaults are used (CI/Censor on; others off).

• rows.columns.panel Integer vector c(nrow, ncol) specifying the grid size.

• title.panel, subtitle.panel, caption.panel Optional strings for panel annotation.

• tag.panel Passed to patchwork::plot_annotation(tag_levels = ...).

• title.plot Optional length-2 character vector, titles for base/inset plots when inset.panel = TRUE.

• legend.position Position of legends: "top", "right", "bottom", "left", or "none".

• legend.collect If TRUE (grid mode), collect legends across subplots.

• inset.panel If TRUE, place the second plot as an inset over the first.

• inset.left, inset.bottom, inset.right, inset.top Numeric positions (0–1) of the inset box.

• inset.align.to One of "panel", "plot", or "full".

• inset.legend.position Legend position for the inset plot (e.g., "none").

• filename.ggsave Character save the composed panel with the path and name specified.

• width.ggsave Numeric specify width of the composed panel.

• height.ggsave Numeric specify height of the composed panel.

• dpi.ggsave Numeric specify dpi of the composed panel.

• print.panel Logical. If TRUE, the composed patchwork object is printed immediately (for interactive use). If FALSE, the object is returned invisibly so that it can be assigned, modified, or saved. Kept for backward compatibility.

• engine Character scalar selecting the internal plotting engine. Currently only "cifplot" is supported and used to construct each panel cifplot_single(). This argument is reserved for future extensions.

• ... Additional arguments forwarded to cifplot (e.g., style, font.family, font.size, etc.). Panel-wise overrides provided via explicit arguments take precedence over ....

polyreg()

• nuisance.model A formula describing the outcome and nuisance covariates, excluding the exposure of interest. The left-hand side must be Event(time, status) or survival::Surv(time, status).
• exposure A character string giving the name of the categorical exposure variable in data.
• strata Optional character string with the name of the stratification variable used to adjust for dependent censoring (default NULL).
• data A data frame containing the outcome, exposure and nuisance covariates referenced by nuisance.model.
• na.action A function specifying the action to take on missing values (default na.omit).
• code.event1 Integer code of the event of interest (default 1).
• code.event2 Integer code of the competing event (default 2).
• code.censoring Integer code of censoring (default 0).
• code.exposure.ref Integer code identifying the reference exposure category (default 0).
• effect.measure1 Character string specifying the effect measure for the primary event. Supported values are "RR", "OR" and "SHR".
• effect.measure2 Character string specifying the effect measure for the competing event. Supported values are "RR", "OR" and "SHR".
• time.point Numeric time point at which the exposure effect is evaluated. Required for survival and competing risk analyses.
• outcome.type Character string selecting the outcome type. Valid values are "competing-risk", "survival", "binomial", "proportional-survival" and "proportional-competing-risk". Defaults to "competing-risk". If NULL (default), the function automatically infers the outcome type from the data: if the event variable has more than two unique levels, "competing-risk" is assumed; otherwise, "survival" is used. You can also use abbreviations such as "S" or "C". Mixed or ambiguous inputs (e.g., c("S", "C")) trigger automatic detection based on the event coding in data.
• conf.int Numeric two-sided level of CIs (default 0.95).
• report.nuisance.parameter Logical if TRUE, the returned object includes estimates of the nuisance model parameters (default FALSE).
• report.optim.convergence Logical if TRUE, optimization convergence summaries are returned (default FALSE).
• report.sandwich.conf Logical or NULL. When TRUE, CIs based on sandwich variance are computed. When FALSE, they are omitted (default TRUE). This CI is default for time-point models ("outcome.type=COMPETING-RISK", "survival" or "binomial") and is not available otherwise.
• report.boot.conf Logical or NULL. When TRUE, bootstrap CIs are computed. When FALSE, they are omitted. If NULL, the function chooses based on outcome.type (default NULL). This CI is default for proportional models (outcome.type="proportional-competing-risk" or "proportional-survival").
• boot.bca Logical indicating the bootstrap CI method. Use TRUE for bias-corrected and accelerated intervals or FALSE for the normal approximation (default to FALSE).
• boot.replications Integer giving the number of bootstrap replications (default to 200).
• boot.seed Numeric seed used for resampling of bootstrap.
• nleqslv.method Character string specifying the solver used in nleqslv(). Available choices are "Broyden" and "Newton".
• optim.parameter1 Numeric tolerance for convergence of the outer loop (default 1e-6).
• optim.parameter2 Numeric tolerance for convergence of the inner loop (default 1e-6).
• optim.parameter3 Numeric constraint on the absolute value of parameters (default 100).
• optim.parameter4 Integer maximum number of outer loop iterations (default 50).
• optim.parameter5 Integer maximum number of nleqslv() iterations per outer iteration (default 50).
• optim.parameter6 Integer maximum number of iterations for the Levenberg-Marquardt routine (default 50).
• optim.parameter7 Numeric convergence tolerance for the Levenberg-Marquardt routine (default 1e-10).
• optim.parameter8 Numeric tolerance for updating the Hessian in the Levenberg-Marquardt routine (default 1e-6).
• optim.parameter9 Numeric starting value for the Levenberg-Marquardt damping parameter lambda (default 1e-6).
• optim.parameter10 Numeric upper bound for lambda in the Levenberg-Marquardt routine (default 40).
• optim.parameter11 Numeric lower bound for lambda in the Levenberg-Marquardt routine (default 0.025).
• optim.parameter12 Numeric multiplicative increment applied to lambda when the Levenberg-Marquardt step is successful (default to 2).
• optim.parameter13 Numeric multiplicative decrement applied to lambda when the Levenberg-Marquardt step is unsuccessful (default 0.5).
• data.initial.values Optional data frame providing starting values for the optimization (default NULL).
• normalize.covariate Logical indicating whether covariates should be centered and scaled prior to optimization (default TRUE).
• terminate.time.point Logical indicating whether time points that contribute estimation are terminated by min of max follow-up times of each exposure level (default TRUE).
• prob.bound Numeric lower bound used to internally truncate probabilities away from 0 and 1 (default 1e-7).