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gen_all_ICC.R
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gen_all_ICC.R
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##-------------------------------------------------------------------------------
## gen_all_ICC: calculate ICCs for the twins and singletons, for the 3-timepoints
## with and without gestational age. Writes output to .csv files.
##
## Syntax: gen_all_ICC()
##
##
## Example:
## > source('gen_all_ICC.R')
## > gen_all_ICC()
##
##
## REQUIRES:
## lme4 (version 1.1.15)
## plyr (version 1.8.4)
##
## and local functions:
## gen_ICCs/load_twin_features.R
## gen_ICCs/do_all_ICCs.R
## gen_ICCs/cal_ICC.R
## gen_ICCs/estimate_ICC.R
## John M. O' Toole, University College Cork
## Started: 22-10-2018
##
## last update: Time-stamp: <2018-10-22 17:50:28 (otoolej)>
##-------------------------------------------------------------------------------
gen_all_ICC <- function(){
##-------------------------------------------------------------------
## load libraries and local files:
##-------------------------------------------------------------------
require(lme4)
require(plyr)
source('set_paths.R')
source(paste(r_files_dir, 'load_twin_features.R', sep=""))
source(paste(r_files_dir, 'do_all_ICCs.R', sep=""))
source(paste(r_files_dir, 'cal_ICC.R', sep=""))
source(paste(r_files_dir, 'estimate_ICC.R', sep=""))
##-------------------------------------------------------------------
## 1.load the data for twins:
##-------------------------------------------------------------------
dfFeats <- load_twin_features(dfNames_fin$twin_feats)
## subsets for MCDA and DCDA infants:
dfFeats.MCDA <- droplevels( subset(dfFeats, (twinType %in% "MCDA")) )
dfFeats.DCDA <- droplevels( subset(dfFeats, (twinType %in% "DCDA")) )
##-------------------------------------------------------------------
## 2. do for all twins, then MCDA and DCDA subsets:
##-------------------------------------------------------------------
do_all_ICCs(dfFeats, dfNames_fout$twin_icc)
do_all_ICCs(dfFeats.MCDA, dfNames_fout$mcda_icc)
do_all_ICCs(dfFeats.DCDA, dfNames_fout$dcda_icc)
##-------------------------------------------------------------------
## 3. same analysis for singletons:
##-------------------------------------------------------------------
## load the data:
dfFeatsSing <- load_twin_features(dfNames_fin$sing_feats)
## estimate the ICCs:
do_all_ICCs(dfFeatsSing, dfNames_fout$sing_icc)
}