This function computes an approximate confidence interval of a point estimate (i.e. the summary statistic).
Usage
computeStandardCI(
obs,
rnd,
conf.level = 0.95,
distribution = c("normal", "t"),
n,
na.rm = FALSE
)Arguments
- obs
a numeric scalar representing the observed value of the summary statistic.
- rnd
numerical vector containing the permutation/bootstrap replication of the statistics.
- conf.level
the desired confidence level.
- distribution
sampling distribution of the estimate. Use
"normal"if the population has unknown mean and known variance (or if the sample sizenis large);"t"if the population variance is unknown and sample size is small.- n
sample size, used to compute the degrees of freedom if
distribution = "t".- na.rm
logical, whether NA values should be removed before computing the standard error. Defaults to
FALSE.
Value
A named numeric vector with 2 elements, lower and upper,
the lower and upper bounds of the confidence interval
for the point estimate.
Details
The confidence interval provides additional information about the variability of a point estimate and it is generally defined as
$$CI = estimate \pm \textit{margin of error} = estimate \pm \textit{critical value} \times \textit{standard error}$$
where \(\textit{estimate}\) is the sample statistic estimating the population parameter of interest; \(\textit{critical value}\) is a value based on the sampling distribution of the estimate and the desired confidence level; \(\textit{standard error}\) is the standard deviation of the point estimate.