prec_riskratio: Sample size or precision for risk ratio
In a-lenz/presize: Precision Based Sample Size Calculation

Description Usage Arguments Details References Examples

View source: R/differences.R

prec_riskratio returns the risk ratio and the sample size or the precision for the provided proportions

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prec_riskratio(p1, p2, n1 = NULL, r = 1, conf.width = NULL,
  conf.level = 0.95, method = c("koopman", "katz"),
  tol = .Machine$double.eps^0.25)

`p1`	Risk among unexposed
`p2`	Risk among exposed
`n1`	Number of patients in unexposed group
`r`	allocation ratio (relative size of unexposed and exposed cohort (`n1` / `n2`))
`conf.width`	precision (the full width of the conficende interval)
`conf.level`	confidence level
`method`	Exactly one of `koopman` (default), `katz`. Methods can be abbreviated.
`tol`	numerical tolerance used in root finding, the default providing (at least) four significant digits

Exactly one of the parameters n1, conf.width must be passed as NULL, and that parameter is determined from the other.

Koopman (koopman) provides an asymptotic score confidence interval that is always consistent with Pearsons chi-squared test. It is the recommended interval (Fagerland et al.).

Katz (katz) use a logarithmic transformation to calculate the confidence interval. The CI cannot be computed if one of the proportions is zero. If both proportions are 1, the estimate of the standard error becomes zero, resulting in a CI of [1, 1].

uniroot is used to solve n for the katz, and koopman method.

Fagerland MW, Lydersen S, and Laake P (2015). Recommended confidence intervals for two independent binomial proportions, Statistical methods in medical research 24(2):224-254.

Katz D, Baptista J, Azen SP, and Pike MC (1978) Obtaining Confidence Intervals for the Risk Ratio in Cohort Studies, Biometrics 34:469-474

Koopman PAR (1984) Confidence Intervals for the Ratio of Two Binomial Proportions, Biometrics 40:513-517

# Validate funciton with example in Fagerland et al. (2015), Table 5.
prec_riskratio(p1 = 7/34, p2 = 1/34, n1 = 34, r = 1, met = "katz")
# 7 (0.91 to 54)
prec_riskratio(p1 = 7/34, p2 = 1/34, n1 = 34, r = 1, met = "koopman")
# 7 (1.21 to 43)

# Validate the Koopman method with example in Koopman (1984)
prec_riskratio(p1 = 36/40, p2 = 16/80, n1 = 40, r = 2, met = "koopman")
# 4.5 (2.94 to 7.15)