Performs univariate survival analysis comparing survival between groups. This analysis calculates person-time follow-up for each group and uses this to derive accurate survival estimates and incidence rates that account for varying follow-up durations across groups. The Cox proportional hazards model incorporates person-time by modeling the hazard function, which represents the instantaneous event rate per unit of person-time.
Usage
survival(
data,
elapsedtime,
tint = FALSE,
dxdate,
fudate,
explanatory,
outcome,
outcomeLevel,
dod,
dooc,
awd,
awod,
analysistype = "overall",
cutp = "12, 36, 60",
timetypedata = "ymd",
timetypeoutput = "months",
uselandmark = FALSE,
landmark = 3,
pw = FALSE,
padjustmethod = "holm",
ph_cox = FALSE,
sc = FALSE,
kmunicate = FALSE,
ce = FALSE,
ch = FALSE,
endplot = 60,
ybegin_plot = 0,
yend_plot = 1,
byplot = 12,
multievent = FALSE,
ci95 = FALSE,
risktable = FALSE,
censored = FALSE,
pplot = TRUE,
medianline = "none",
person_time = FALSE,
time_intervals = "12, 36, 60",
rate_multiplier = 100,
rmst_analysis = FALSE,
rmst_tau = 0,
stratified_cox = FALSE,
strata_variable,
residual_diagnostics = FALSE,
export_survival_data = FALSE,
loglog = FALSE
)Arguments
- data
The data as a data frame.
- elapsedtime
The time elapsed from the start of the study to the event or censoring.
- tint
If the time is in date format, select this option to calculate the survival time. The time will be calculated as the difference between the event date and the diagnosis date. If the follow-up date is available, the time will be calculated as the difference between the event date and the follow-up date.
- dxdate
The date of diagnosis. If the time is in date format, the time will be calculated as the difference between the event date and the diagnosis date.
- fudate
The date of follow-up. If the time is in date format, the time will be calculated as the difference between the event date and the follow-up date.
- explanatory
The explanatory variable that will be used to compare the survival times of different groups.
- outcome
The outcome variable that will be used to compare the survival times of different groups.
- outcomeLevel
The level of the outcome variable that will be used as the event level.
- dod
.
- dooc
.
- awd
.
- awod
.
- analysistype
.
- cutp
.
- timetypedata
select the time type in data
- timetypeoutput
select the time type in output
- uselandmark
.
- landmark
.
- pw
.
- padjustmethod
.
- ph_cox
.
- sc
.
- kmunicate
.
- ce
.
- ch
.
- endplot
.
- ybegin_plot
.
- yend_plot
.
- byplot
.
- multievent
.
- ci95
.
- risktable
.
- censored
.
- pplot
.
- medianline
If true, displays a line indicating the median survival time on the survival plot.
- person_time
Enable this option to calculate and display person-time metrics, including total follow-up time and incidence rates. These metrics help quantify the rate of events per unit of time in your study population.
- time_intervals
Specify time intervals for stratified person-time analysis. Enter a comma-separated list of time points to create intervals. For example, "12, 36, 60" will create intervals 0-12, 12-36, 36-60, and 60+.
- rate_multiplier
Specify the multiplier for incidence rates (e.g., 100 for rates per 100 person-years, 1000 for rates per 1000 person-years).
- rmst_analysis
Calculate Restricted Mean Survival Time, which represents the average survival time up to a specified time horizon. Useful when median survival cannot be estimated or for comparing survival over a specific time period.
- rmst_tau
Time horizon for RMST calculation. If 0 or not specified, uses the 75th percentile of follow-up time. Should be specified in the same units as the survival time.
- stratified_cox
Perform stratified Cox regression to account for non-proportional hazards or unmeasured confounders that affect baseline hazard.
- strata_variable
Variable to use for stratification in Cox regression. This variable should represent groups with different baseline hazards.
- residual_diagnostics
Calculate and display Cox model residuals for diagnostic purposes, including Martingale, deviance, score, and Schoenfeld residuals.
- export_survival_data
Export detailed survival estimates for external analysis, including survival probabilities, confidence intervals, and risk tables at multiple time points.
- loglog
Display log-log survival plot for visual assessment of proportional hazards assumption. Parallel lines suggest proportional hazards.
Value
A results object containing:
results$subtitle | a preformatted | ||||
results$todo | a html | ||||
results$medianSummary | a preformatted | ||||
results$medianTable | a table | ||||
results$coxSummary | a preformatted | ||||
results$coxTable | a table | ||||
results$tCoxtext2 | a html | ||||
results$cox_ph | a preformatted | ||||
results$plot8 | an image | ||||
results$survTableSummary | a preformatted | ||||
results$survTable | a table | ||||
results$personTimeTable | a table | ||||
results$personTimeSummary | a html | ||||
results$rmstTable | a table | ||||
results$rmstSummary | a preformatted | ||||
results$residualsTable | a table | ||||
results$survivalExport | an output | ||||
results$survivalExportSummary | a html | ||||
results$pairwiseSummary | a preformatted | ||||
results$pairwiseTable | a table | ||||
results$plot | an image | ||||
results$plot2 | an image | ||||
results$plot3 | an image | ||||
results$plot6 | an image | ||||
results$plot7 | an image | ||||
results$residualsPlot | an image | ||||
results$calculatedtime | an output | ||||
results$outcomeredefined | an output |
Tables can be converted to data frames with asDF or as.data.frame. For example:
results$medianTable$asDF
as.data.frame(results$medianTable)