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R
epiR

epi.descriptives

Descriptive statistics

Description

Computes descriptive statistics from a vector of numbers.

Usage

epi.descriptives(dat, conf.level = 0.95)

Arguments

dat

vector for which descriptive statistics will be calculated.
conf.level

magnitude of the returned confidence intervals. Must be a single number between 0 and 1.

Value

A list containing the following:

arithmetic

n number of observations, mean arithmetic mean, sd arithmetic standard deviation, q25 25th quantile, q50 50th quantile, q75 75th quantile, lower lower bound of the confidence interval, upper upper bound of the confidence interval, min minimum value, max maximum value, and na number of missing values.
geometric

n number of observations, mean geometric mean, sd geometric standard deviation, q25 25th quantile, q50 50th quantile, q75 75th quantile, lower lower bound of the confidence interval, upper upper bound of the confidence interval, min minimum value, max maximum value, and na number of missing values.
symmetry

skewness and kurtosis.

Examples

id <- 1:1000
tmp <- rnorm(1000, mean = 0, sd = 1)
id <- sample(id, size = 20)
tmp[id] <- NA

epi.descriptives(tmp, conf.level = 0.95)
epiR

Tools for the Analysis of Epidemiological Data

v2.0.19
GPL (>= 2)
Authors
Mark Stevenson <mark.stevenson1@unimelb.edu.au> and Evan Sergeant <evansergeant@gmail.com> with contributions from Telmo Nunes, Cord Heuer, Jonathon Marshall, Javier Sanchez, Ron Thornton, Jeno Reiczigel, Jim Robison-Cox, Paola Sebastiani, Peter Solymos, Kazuki Yoshida, Geoff Jones, Sarah Pirikahu, Simon Firestone, Ryan Kyle, Johann Popp, Mathew Jay and Charles Reynard.
Initial release
2021-01-12

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