ci2ms: Effect size and standard error from confidence interval

In gap: Genetic Analysis Package

Effect size and standard error from confidence interval

Description

Effect size and standard error from confidence interval

Usage

ci2ms(ci, logscale = TRUE, alpha = 0.05)

Arguments

ci	confidence interval (CI). The delimiter between lower and upper limit is either a hyphen (-) or en dash (–).
logscale	a flag indicating the confidence interval is based on a log-scale.
alpha	Type 1 error.

Details

Effect size is a measure of strength of the relationship between two variables in a population or parameter estimate of that population. Without loss of generality, denote m and s to be the mean and standard deviation of a sample from N(\mu,\sigma^2)). Let z \sim N(0,1) with cutoff point z_\alpha, confidence limits L, U in a CI are defined as follows,

\begin{aligned} L & = m - z_\alpha s \cr U & = m + z_\alpha s \end{aligned}

\Rightarrow U + L = 2 m, U - L=2 z_\alpha s. Consequently,

\begin{aligned} m & = \frac{U + L}{2} \cr s & = \frac{U - L}{2 z_\alpha} \end{aligned}

Effect size in epidemiological studies on a binary outcome is typically reported as odds ratio from a logistic regression or hazard ratio from a Cox regression, L\equiv\log(L), U\equiv\log(U).

Value

Based on CI, the function provides a list containing estimates

• m effect size (log(OR))

• s standard error

• direction a decrease/increase (-/+) sign such that sign(m)=-1, 0, 1, is labelled "-", "0", "+", respectively as in PhenoScanner.

Examples

# rs3784099 and breast cancer recurrence/mortality
ms <- ci2ms("1.28-1.72")
print(ms)
# Vector input
ci2 <- c("1.28-1.72","1.25-1.64")
ms2 <- ci2ms(ci2)
print(ms2)

gap documentation built on Aug. 26, 2023, 5:07 p.m.