mirror of
https://github.com/dchakro/shared_Rscripts.git
synced 2026-05-17 09:12:16 -07:00
79 lines
3.1 KiB
R
79 lines
3.1 KiB
R
# Installing missing dependencies
|
|
dependencies <- c("plyr")
|
|
missing_packages <- dependencies[!(dependencies %in% installed.packages()[, "Package"])]
|
|
if(length(missing_packages)) install.packages(missing_packages)
|
|
rm(missing_packages,dependencies)
|
|
|
|
summarySE <- function(data=NULL, measurevar=NULL, statistic="mean", groupvars=NULL, na.rm=FALSE, conf.interval=.95, .drop=TRUE) {
|
|
# #<---------------------------->
|
|
# # You must include this section when:
|
|
# # Distributing, Using and/or Modifying this code.
|
|
# # Please read and abide by the terms of the included LICENSE.
|
|
# # Copyright 2018, Deepankar Chakroborty, All rights reserved.
|
|
|
|
# # Author : Deepankar Chakroborty (https://github.com/dchakro)
|
|
# # Website: https://www.dchakro.com
|
|
# # Report issues: https://github.com/dchakro/shared_Rscripts/issues
|
|
# # License: https://github.com/dchakro/shared_Rscripts/blob/master/LICENSE
|
|
|
|
# # Adapted from: http://www.cookbook-r.com/Manipulating_data/Summarizing_data/
|
|
|
|
# # PURPOSE:
|
|
# # Summarizes data by returning count, mean, standard deviation,
|
|
# # standard error of the mean, and confidence interval (default 95%)
|
|
# # for a given data frame based on grouping variables
|
|
# # data: a data frame.
|
|
|
|
# # PARAMETERS
|
|
# # measurevar: the name of a column that contains the variable to be summariezed
|
|
# # groupvars: a vector containing names of columns that contain grouping variables
|
|
# # na.rm: a boolean that indicates whether to ignore NA's
|
|
# # conf.interval: the percent range of the confidence interval (default is 95%)
|
|
# #<---------------------------->
|
|
|
|
# a version of length which can handle NA's: if na.rm==T, don't count them
|
|
length2 <- function (x, na.rm=FALSE) {
|
|
if (na.rm) sum(!is.na(x))
|
|
else length(x)
|
|
}
|
|
|
|
# This does the summary. For each group's data frame, return a vector with
|
|
# N, mean, and sd
|
|
if(statistic=="mean"){
|
|
datac <- plyr::ddply(data, groupvars, .drop=.drop,
|
|
.fun = function(xx, col) {
|
|
c(N = length2(xx[[col]], na.rm=na.rm),
|
|
mean = mean (xx[[col]], na.rm=na.rm),
|
|
sd = sd (xx[[col]], na.rm=na.rm)
|
|
)
|
|
},
|
|
measurevar
|
|
)
|
|
# Rename the "mean" column
|
|
datac <- plyr::rename(datac, c("mean" = measurevar))
|
|
}
|
|
if(statistic=="median"){
|
|
datac <- plyr::ddply(data, groupvars, .drop=.drop,
|
|
.fun = function(xx, col) {
|
|
c(N = length2(xx[[col]], na.rm=na.rm),
|
|
median = median (xx[[col]], na.rm=na.rm),
|
|
sd = sd (xx[[col]], na.rm=na.rm)
|
|
)
|
|
},
|
|
measurevar
|
|
)
|
|
# Rename the "median" column
|
|
datac <- plyr::rename(datac, c("median" = measurevar))
|
|
}
|
|
|
|
# Calculate standard error of the mean
|
|
datac$se <- datac$sd / sqrt(datac$N)
|
|
|
|
# Confidence interval multiplier for standard error
|
|
# Calculate t-statistic for confidence interval:
|
|
# e.g., if conf.interval is .95, use .975 (above/below), and use df=N-1
|
|
ciMult <- qt(conf.interval/2 + .5, datac$N-1)
|
|
datac$ci <- datac$se * ciMult
|
|
|
|
return(datac)
|
|
}
|