calculate_prevalence: Title of the function

In Hackout2/mapData: Tools to help with mapping outbreak data

Description

This is what the function does bla bla bla.

Usage

calculate_prevalence(data, pops = NULL, conf.level = 0.95,
  region.head = "region", scale = 1)

Arguments

data	A line list-type data frame (one line per case), including a column with the region in which the case occurred
pops	A data frame containing one line per region in data, with first column for region name and second for population
conf.level	Level of confidence interval required for prevalence estimates.
region.head	A string containing the name of the column specifying the region for each case
scale	Scaling with which to report prevalence (per head, per 100 000, etc.)

Value

A data frame containing total population, number of cases and prevalence by region

Examples

my.data <- data.frame(county.id = ceiling(3*runif(10)),
                     age = rlnorm(10),
			sex = factor(floor(2*runif(10)), levels=c(0,1), labels=c("male", "female"))
                     )

my.populations <- data.frame(county.id = 1:3,
				population = c(10, 50, 100)
				)

# example without population of each region
calculate_prevalence(my.data, region.head="county.id")

# example with populations
calculate_prevalence(my.data, region.head="county.id", pops=my.populations)

Hackout2/mapData documentation built on May 6, 2019, 9:48 p.m.