xgx_conf_int returns a dataframe with mean +/- confidence intervals

Source: R/xgx_stat_ci.R

xgx_conf_int returns a dataframe with mean +/- confidence intervals

xgx_conf_int(y, conf_level = 0.95, distribution = "normal", ci_method = NULL)

Arguments

y

data to compute confidence interval of

conf_level

The percentile for the confidence interval (should fall between 0 and 1). The default is 0.95, which corresponds to a 95 percent confidence interval.

distribution

The distribution which the data follow, used for calculating confidence intervals. The options are "normal", "lognormal", and "binomial". The "normal" option will use the Student t Distribution to calculate confidence intervals, the "lognormal" option will transform data to the log space first. The "binomial" option will use the binom.confint function to calculate the confidence intervals. Note: binomial data must be numeric and contain only 1's and 0's. The "multinomial" or "ordinal" options will use DescTools::MultinomCI

ci_method

Method to pass to binom.confint or MultinomCI. Defaults are "exact" and "goodman", respectively.

Value

data.frame

Examples

# default settings for normally distributed data, 95% confidence interval,  
data <- data.frame(x = rep(c(1, 2, 3), each = 20),
                   y = rep(c(1, 2, 3), each = 20) + stats::rnorm(60),
                   group = rep(1:3, 20))
xgx_conf_int(data$y)
#>          y     ymin     ymax
#> 1 1.717784 1.382446 2.053123