Calculates confidence intervals for the mean of a normally-distributed variable.
ciMean(x, conf = 0.95, na.rm = FALSE)A numeric vector, data frame or matrix containing the observations.
The level of confidence desired. Defaults to a 95% confidence interval
Logical value indicating whether missing values are to be removed. Defaults to FALSE.
The output is a matrix containing the lower and upper ends of the confidence interval for each variable. If a data frame is specified as input and contains non-numeric variables, the corresponding rows in the output matrix have NA values.
This function calculates the confidence interval for the mean of
a variable (or set of variables in a data frame or matrix), under the
standard assumption that the data are normally distributed. By default it
returns a 95% confidence interval (conf = 0.95) and does not
remove missing values (na.rm = FALSE).
X <- c(1, 3, 6) # data
ciMean(X) # 95 percent confidence interval
#> 2.5% 97.5%
#> X -2.918276 9.584943
ciMean(X, conf = .8) # 80 percent confidence interval
#> 10% 90%
#> X 0.5935938 6.073073
confint( lm(X ~ 1) ) # for comparison purposes
#> 2.5 % 97.5 %
#> (Intercept) -2.918276 9.584943
X <- c(1, 3, NA, 6) # data with missing values
ciMean(X, na.rm = TRUE) # remove missing values
#> 2.5% 97.5%
#> X -2.918276 9.584943