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## ----output, include=FALSE----------------------------------------------------
knitr::opts_chunk$set(echo = TRUE)
## ----setup, message = FALSE, warning = FALSE----------------------------------
# source functions required
library(PHEindicatormethods)
library(dplyr)
## ----default_example----------------------------------------------------------
# Pass data through SII function ---------------------------------------
LE_data_SII <- LE_data %>%
# Group the input dataframe to create subgroups to calculate the SII for
group_by(Sex, GeoCode) %>%
# Run SII function on grouped dataset
phe_sii(quantile = Decile,
population = Pop ,
value = LifeExp,
value_type = 0, # specify default indicator type
confidence = c(0.95, 0.998),
se = SE,
repetitions = 1000,
rii = FALSE,
type = "full") # use smaller no. of repetitions e.g. for testing
# View first 10 rows of results
knitr::kable(head(LE_data_SII, 10))
## ----rate_example-------------------------------------------------------------
# Pass data through SII function ---------------------------------------
DSR_data_SII <- DSR_data %>%
# Group the input dataframe to create subgroups to calculate the SII for
group_by(Period) %>%
# Run SII function on grouped dataset
phe_sii(quantile = Quintile,
population = total_pop ,
value = value,
value_type = 1, # specifies indicator is a rate
lower_cl = lowercl,
upper_cl = uppercl,
transform = TRUE,
rii = TRUE, # returns RII as well as SII (default is FALSE)
reliability_stat = TRUE) # returns reliability stats (default is FALSE)
# View results
knitr::kable(DSR_data_SII)
## ----proportion_example-------------------------------------------------------
# Pass data through SII function ---------------------------------------
prevalence_SII <- prevalence_data %>%
# Group the input dataframe to create subgroups to calculate the SII for
group_by(Period, SchoolYear, AreaCode) %>%
# Format prevalences to be between 0 and 1
mutate(Rate = Rate/100,
LCL = LCL/100,
UCL = UCL/100) %>%
# Run SII function on grouped dataset
phe_sii(quantile = Decile,
population = Measured,
value = Rate,
value_type = 2, # specifies indicator is a proportion
lower_cl = LCL,
upper_cl = UCL,
transform = TRUE,
multiplier = -100) # negative multiplier to scale SII outputs
# View first 10 rows of results
knitr::kable(head(prevalence_SII,10))
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