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One-Sample Survival Study Sample Size or Power Calculation

Source: R/oneSurvSampleSize.R
oneSurvSampleSize.Rd

Calculates the required sample size or power for a single-arm survival study using various transformation-based methods, including arcsine-square root, log-log, logit, and others. This function assumes an exponential survival model.

Usage

oneSurvSampleSize(
  survTime,
  p1,
  p2,
  accrualTime,
  followTime,
  alpha,
  power,
  side = c("two.sided", "one.sided"),
  method = c("arcsin", "log-log", "logit", "log", "log-swog", "identity")
)

Arguments

survTime

Time point at which survival is evaluated (e.g., median follow-up time).

p1

Expected survival probability under the alternative hypothesis.

p2

Survival probability under the null hypothesis.

accrualTime

Patient accrual period.

followTime

Additional follow-up period after accrual ends.

alpha

Significance level (e.g., 0.05).

power

Desired statistical power (e.g., 0.8).

side

Type of hypothesis test. Either "two.sided" (default) or "one.sided".

method

Transformation method for comparison. One of "arcsin", "log-log", "logit", "log", "log-swog", "identity".

Value

A named numeric vector with:

SampleSize

Calculated required sample size.

Power

Achieved power with the calculated sample size.

References

Fleming TR, Harrington DP. (1991). Counting Processes and Survival Analysis. New York: Wiley, pp. 236–237, Example 6.3.1.

Andersen PK, Borgan O, Gill RD, Keiding N. (1993). Statistical Models Based on Counting Processes. New York: Springer-Verlag, pp. 176–287, Section IV.1–3.

Bie O, Borgan O, Liestol K. (1987). Confidence intervals and confidence bands for the cumulative hazard rate function and their small sample properties. Scandinavian Journal of Statistics, 14(3), 221–233.

Borgan O, Liestol K. (1990). A note on confidence intervals and bands for the survival function based on transformations. Scandinavian Journal of Statistics, 17(1), 35–41.

Nagashima K, Noma H, Sato Y, Gosho M. (2020). Sample size calculations for single-arm survival studies using transformations of the Kaplan–Meier estimator. Pharmaceutical Statistics. https://doi.org/10.1002/pst.2090 Available at: https://arxiv.org/abs/2012.03355

Web calculator (One-sample): https://nshi.jp/en/js/onesurvyr/

Examples

oneSurvSampleSize(
  survTime = 2,
  p1 = 0.75,
  p2 = 0.6,
  accrualTime = 1,
  followTime = 1,
  alpha = 0.05,
  power = 0.8,
  side = "two.sided",
  method = "log-log"
)
#> SampleSize      Power 
#>        Inf        NaN