R/mxc_bmi.R
In SindisoNyathi/GOPCMxC:
#' @title MxC BMI Function
#' @author Sindiso Nyathi
#' @description This function will run the BMI analysis portions of the Mexico Analysis.
#' @param home Parent directory path.
#' @param filename String name of file with the runs eg. "Baseline"
#' @return Will write multiple csv files into the Folders with the experiments.
#' @details This function will read in the folder with the runs, and read in each run. Then
#' call mxc_bmiind which will find the numbers/percentages of people OWO for each age and gender
#' grouping we are interested in.
#'mxc_bmi()
#'
#'@seealso {\code{\link{mxc_master}}, \code{\link{mxc_bmiind}}}
#'@examples
#'mxc_bmi(home, "Baseline")
#'mxc_bmi(home, "Intervention 1")
#'@family
#'
#' @export
mxc_bmi <- function(home, filename) {
#Set the Working directory to input folder.
setwd(paste(home, filename, "/", sep = ""))
#Set the constants. Run is the number of runs in the folder.
run = length(list.files(pattern = ".csv$"))
sim = 5 #In years.
#Create the dataframe that you will store the results in.
#This first one stores the raw results for each of the N runs.
mulruns <- data.frame(RunNo. = numeric(run),
#Overall
"Overall. BMI Mean Start" = numeric(run), "Overall. BMI Mean End" = numeric(run), "Overall. BMI Change" = numeric(run),
"Overall. Perc Mean Start" = numeric(run), "Overall. Perc Mean End" = numeric(run), "Overall. Perc Change" = numeric(run),
"Overall. Prop OW Start" = numeric(run), "Overall. Prop OW End" = numeric(run), "Overall. Prop OW Change" = numeric(run),
"Overall. Prop OB Start" = numeric(run), "Overall. Prop OB End" = numeric(run), "Overall. Prop OB Change" = numeric(run),
"Overall. Prop OWO Start" = numeric(run), "Overall. Prop OWO End" = numeric(run), "Overall. Prop OWO Change" = numeric(run),
"Overall. Sample Size" = numeric(run),
#Female
"F BMI Mean Start" = numeric(run), "F BMI Mean End" = numeric(run), "F BMI Change" = numeric(run),
"F Perc Mean Start" = numeric(run), "F Perc Mean End" = numeric(run), "F Perc Change" = numeric(run),
"F Prop OW Start" = numeric(run), "F Prop OW End" = numeric(run), "F Prop OW Change" = numeric(run),
"F Prop OB Start" = numeric(run), "F Prop OB End" = numeric(run), "F Prop OB Change" = numeric(run),
"F Prop OWO Start" = numeric(run), "F Prop OWO End" = numeric(run), "F Prop OWO Change" = numeric(run),
"F Sample Size" = numeric(run),
#Male
"M BMI Mean Start" = numeric(run), "M BMI Mean End" = numeric(run), "M BMI Change" = numeric(run),
"M Perc Mean Start" = numeric(run), "M Perc Mean End" = numeric(run), "M Perc Change" = numeric(run),
"M Prop OW Start" = numeric(run), "M Prop OW End" = numeric(run), "M Prop OW Change" = numeric(run),
"M Prop OB Start" = numeric(run), "M Prop OB End" = numeric(run), "M Prop OB Change" = numeric(run),
"M Prop OWO Start" = numeric(run), "M Prop OWO End" = numeric(run), "M Prop OWO Change" = numeric(run),
"M Sample Size" = numeric(run),
#Females, 6 - 9
"F 6-9. BMI Mean Start" = numeric(run), "F 6-9. BMI Mean End" = numeric(run), "F 6-9. BMI Change" = numeric(run),
"F 6-9. Perc Mean Start" = numeric(run), "F 6-9. Perc Mean End" = numeric(run), "F 6-9. Perc Change" = numeric(run),
"F 6-9. Prop OW Start" = numeric(run), "F 6-9. Prop OW End" = numeric(run), "F 6-9. Prop OW Change" = numeric(run),
"F 6-9. Prop OB Start" = numeric(run), "F 6-9. Prop OB End" = numeric(run), "F 6-9. Prop OB Change" = numeric(run),
"F 6-9. Prop OWO Start" = numeric(run), "F 6-9. Prop OWO End" = numeric(run), "F 6-9. Prop OWO Change" = numeric(run),
"F 6-9. Sample Size" = numeric(run),
#Males, 6 - 9
"M 6-9. BMI Mean Start" = numeric(run), "M 6-9. BMI Mean End" = numeric(run), "F 6-9. BMI Change" = numeric(run),
"M 6-9. Perc Mean Start" = numeric(run), "M 6-9. Perc Mean End" = numeric(run), "F 6-9. Perc Change" = numeric(run),
"M 6-9. Prop OW Start" = numeric(run), "M 6-9. Prop OW End" = numeric(run), "M 6-9. Prop OW Change" = numeric(run),
"M 6-9. Prop OB Start" = numeric(run), "M 6-9. Prop OB End" = numeric(run), "M 6-9. Prop OB Change" = numeric(run),
"M 6-9. Prop OWO Start" = numeric(run), "M 6-9. Prop OWO End" = numeric(run), "M 6-9. Prop OWO Change" = numeric(run),
"M 6-9. Sample Size" = numeric(run),
#Females 10 - 14
"F 10-14. BMI Mean Start" = numeric(run), "F 10-14. BMI Mean End" = numeric(run), "F 10-14. BMI Change" = numeric(run),
"F 10-14. Perc Mean Start" = numeric(run), "F 10-14. Perc Mean End" = numeric(run), "F 10-14. Perc Change" = numeric(run),
"F 10-14. Prop OW Start" = numeric(run), "F 10-14. Prop OW End" = numeric(run), "F 10-14. Prop OW Change" = numeric(run),
"F 10-14. Prop OB Start" = numeric(run), "F 10-14. Prop OB End" = numeric(run), "F 10-14. Prop OB Change" = numeric(run),
"F 10-14. Prop OWO Start" = numeric(run), "F 10-14. Prop OWO End" = numeric(run), "F 10-14. Prop OWO Change" = numeric(run),
"F 10-14. Sample Size" = numeric(run),
#Male 10 - 14
"M 10-14. BMI Mean Start" = numeric(run), "M 10-14. BMI Mean End" = numeric(run), "M 10-14. BMI Change" = numeric(run),
"M 10-14. Perc Mean Start" = numeric(run), "M 10-14. Perc Mean End" = numeric(run), "M 10-14. Perc Change" = numeric(run),
"M 10-14. Prop OW Start" = numeric(run), "M 10-14. Prop OW End" = numeric(run), "M 10-14. Prop OW Change" = numeric(run),
"M 10-14. Prop OB Start" = numeric(run), "M 10-14. Prop OB End" = numeric(run), "M 10-14. Prop OB Change" = numeric(run),
"M 10-14. Prop OWO Start" = numeric(run), "M 10-14. Prop OWO End" = numeric(run), "M 10-14. Prop OWO Change" = numeric(run),
"M 10-14. Sample Size" = numeric(run),
#Female 15 - 18
"F 15-18. BMI Mean Start" = numeric(run), "F 15-18. BMI Mean End" = numeric(run), "F 15-18. BMI Change" = numeric(run),
"F 15-18. Perc Mean Start" = numeric(run), "F 15-18. Perc Mean End" = numeric(run), "F 15-18. Perc Change" = numeric(run),
"F 15-18. Prop OW Start" = numeric(run), "F 15-18. Prop OW End" = numeric(run), "F 15-18. Prop OW Change" = numeric(run),
"F 15-18. Prop OB Start" = numeric(run), "F 15-18. Prop OB End" = numeric(run), "F 15-18. Prop OB Change" = numeric(run),
"F 15-18. Prop OWO Start" = numeric(run), "F 15-18. Prop OWO End" = numeric(run), "F 15-18. Prop OWO Change" = numeric(run),
"F 15-18. Sample Size" = numeric(run),
#Male 15 - 18
"M 15-18. BMI Mean Start" = numeric(run), "M 15-18. BMI Mean End" = numeric(run), "M 15-18. BMI Change" = numeric(run),
"M 15-18. Perc Mean Start" = numeric(run), "M 15-18. Perc Mean End" = numeric(run), "M 15-18. Perc Change" = numeric(run),
"M 15-18. Prop OW Start" = numeric(run), "M 15-18. Prop OW End" = numeric(run), "M 15-18. Prop OW Change" = numeric(run),
"M 15-18. Prop OB Start" = numeric(run), "M 15-18. Prop OB End" = numeric(run), "M 15-18. Prop OB Change" = numeric(run),
"M 15-18. Prop OWO Start" = numeric(run), "M 15-18. Prop OWO End" = numeric(run), "M 15-18. Prop OWO Change" = numeric(run),
"M 15-18. Sample Size" = numeric(run)
)
mulrunsSD <- data.frame(RunNo. = numeric(run),
#Overall
"Overall. BMI Mean Start" = numeric(run), "Overall. BMI Mean End" = numeric(run), "Overall. BMI Change" = numeric(run),
"Overall. Perc Mean Start" = numeric(run), "Overall. Perc Mean End" = numeric(run), "Overall. Perc Change" = numeric(run),
"Overall. Prop OW Start" = numeric(run), "Overall. Prop OW End" = numeric(run), "Overall. Prop OW Change" = numeric(run),
"Overall. Prop OB Start" = numeric(run), "Overall. Prop OB End" = numeric(run), "Overall. Prop OB Change" = numeric(run),
"Overall. Prop OWO Start" = numeric(run), "Overall. Prop OWO End" = numeric(run), "Overall. Prop OWO Change" = numeric(run),
"Overall. Sample Size" = numeric(run),
#Female
"F BMI Mean Start" = numeric(run), "F BMI Mean End" = numeric(run), "F BMI Change" = numeric(run),
"F Perc Mean Start" = numeric(run), "F Perc Mean End" = numeric(run), "F Perc Change" = numeric(run),
"F Prop OW Start" = numeric(run), "F Prop OW End" = numeric(run), "F Prop OW Change" = numeric(run),
"F Prop OB Start" = numeric(run), "F Prop OB End" = numeric(run), "F Prop OB Change" = numeric(run),
"F Prop OWO Start" = numeric(run), "F Prop OWO End" = numeric(run), "F Prop OWO Change" = numeric(run),
"F Sample Size" = numeric(run),
#Male
"M BMI Mean Start" = numeric(run), "M BMI Mean End" = numeric(run), "M BMI Change" = numeric(run),
"M Perc Mean Start" = numeric(run), "M Perc Mean End" = numeric(run), "M Perc Change" = numeric(run),
"M Prop OW Start" = numeric(run), "M Prop OW End" = numeric(run), "M Prop OW Change" = numeric(run),
"M Prop OB Start" = numeric(run), "M Prop OB End" = numeric(run), "M Prop OB Change" = numeric(run),
"M Prop OWO Start" = numeric(run), "M Prop OWO End" = numeric(run), "M Prop OWO Change" = numeric(run),
"M Sample Size" = numeric(run),
#Females, 6 - 9
"F 6-9. BMI Mean Start" = numeric(run), "F 6-9. BMI Mean End" = numeric(run), "F 6-9. BMI Change" = numeric(run),
"F 6-9. Perc Mean Start" = numeric(run), "F 6-9. Perc Mean End" = numeric(run), "F 6-9. Perc Change" = numeric(run),
"F 6-9. Prop OW Start" = numeric(run), "F 6-9. Prop OW End" = numeric(run), "F 6-9. Prop OW Change" = numeric(run),
"F 6-9. Prop OB Start" = numeric(run), "F 6-9. Prop OB End" = numeric(run), "F 6-9. Prop OB Change" = numeric(run),
"F 6-9. Prop OWO Start" = numeric(run), "F 6-9. Prop OWO End" = numeric(run), "F 6-9. Prop OWO Change" = numeric(run),
"F 6-9. Sample Size" = numeric(run),
#Males, 6 - 9
"M 6-9. BMI Mean Start" = numeric(run), "M 6-9. BMI Mean End" = numeric(run), "F 6-9. BMI Change" = numeric(run),
"M 6-9. Perc Mean Start" = numeric(run), "M 6-9. Perc Mean End" = numeric(run), "F 6-9. Perc Change" = numeric(run),
"M 6-9. Prop OW Start" = numeric(run), "M 6-9. Prop OW End" = numeric(run), "M 6-9. Prop OW Change" = numeric(run),
"M 6-9. Prop OB Start" = numeric(run), "M 6-9. Prop OB End" = numeric(run), "M 6-9. Prop OB Change" = numeric(run),
"M 6-9. Prop OWO Start" = numeric(run), "M 6-9. Prop OWO End" = numeric(run), "M 6-9. Prop OWO Change" = numeric(run),
"M 6-9. Sample Size" = numeric(run),
#Females 10 - 14
"F 10-14. BMI Mean Start" = numeric(run), "F 10-14. BMI Mean End" = numeric(run), "F 10-14. BMI Change" = numeric(run),
"F 10-14. Perc Mean Start" = numeric(run), "F 10-14. Perc Mean End" = numeric(run), "F 10-14. Perc Change" = numeric(run),
"F 10-14. Prop OW Start" = numeric(run), "F 10-14. Prop OW End" = numeric(run), "F 10-14. Prop OW Change" = numeric(run),
"F 10-14. Prop OB Start" = numeric(run), "F 10-14. Prop OB End" = numeric(run), "F 10-14. Prop OB Change" = numeric(run),
"F 10-14. Prop OWO Start" = numeric(run), "F 10-14. Prop OWO End" = numeric(run), "F 10-14. Prop OWO Change" = numeric(run),
"F 10-14. Sample Size" = numeric(run),
#Male 10 - 14
"M 10-14. BMI Mean Start" = numeric(run), "M 10-14. BMI Mean End" = numeric(run), "M 10-14. BMI Change" = numeric(run),
"M 10-14. Perc Mean Start" = numeric(run), "M 10-14. Perc Mean End" = numeric(run), "M 10-14. Perc Change" = numeric(run),
"M 10-14. Prop OW Start" = numeric(run), "M 10-14. Prop OW End" = numeric(run), "M 10-14. Prop OW Change" = numeric(run),
"M 10-14. Prop OB Start" = numeric(run), "M 10-14. Prop OB End" = numeric(run), "M 10-14. Prop OB Change" = numeric(run),
"M 10-14. Prop OWO Start" = numeric(run), "M 10-14. Prop OWO End" = numeric(run), "M 10-14. Prop OWO Change" = numeric(run),
"M 10-14. Sample Size" = numeric(run),
#Female 15 - 18
"F 15-18. BMI Mean Start" = numeric(run), "F 15-18. BMI Mean End" = numeric(run), "F 15-18. BMI Change" = numeric(run),
"F 15-18. Perc Mean Start" = numeric(run), "F 15-18. Perc Mean End" = numeric(run), "F 15-18. Perc Change" = numeric(run),
"F 15-18. Prop OW Start" = numeric(run), "F 15-18. Prop OW End" = numeric(run), "F 15-18. Prop OW Change" = numeric(run),
"F 15-18. Prop OB Start" = numeric(run), "F 15-18. Prop OB End" = numeric(run), "F 15-18. Prop OB Change" = numeric(run),
"F 15-18. Prop OWO Start" = numeric(run), "F 15-18. Prop OWO End" = numeric(run), "F 15-18. Prop OWO Change" = numeric(run),
"F 15-18. Sample Size" = numeric(run),
#Male 15 - 18
"M 15-18. BMI Mean Start" = numeric(run), "M 15-18. BMI Mean End" = numeric(run), "M 15-18. BMI Change" = numeric(run),
"M 15-18. Perc Mean Start" = numeric(run), "M 15-18. Perc Mean End" = numeric(run), "M 15-18. Perc Change" = numeric(run),
"M 15-18. Prop OW Start" = numeric(run), "M 15-18. Prop OW End" = numeric(run), "M 15-18. Prop OW Change" = numeric(run),
"M 15-18. Prop OB Start" = numeric(run), "M 15-18. Prop OB End" = numeric(run), "M 15-18. Prop OB Change" = numeric(run),
"M 15-18. Prop OWO Start" = numeric(run), "M 15-18. Prop OWO End" = numeric(run), "M 15-18. Prop OWO Change" = numeric(run),
"M 15-18. Sample Size" = numeric(run)
)
#Use a for loop to iterate through all the runs.
for (i in 1:run) {
#read in a run, and process the BMI for that run
runN <- read.csv(paste("mxc run_", i, ".csv", sep = ""))
#Substract the age in the runs from the simulation length.
runN$age = runN$initial_age
#Change the column names for the runs.
runN["bmi_S"] <- runN$initial_bmi
runN["bmi_E"] <- runN$final_bmi
runN["perc_S"] <- runN$initial_bmi_percentile
runN["perc_E"] <- runN$final_bmi_percentile
#Columns for BMI/Percentile change.
runN["delta_bmi"] <- runN$bmi_E - runN$bmi_S
runN["delta_perc"] <- runN$perc_E - runN$perc_S
#Make the subrun files for each age and gender combo..
run_f <- dplyr::filter(runN, gender == "FEMALE")
run_m <- dplyr::filter(runN, gender == "MALE")
run_f6_9 <- dplyr::filter(runN, gender == "FEMALE", age < 10)
run_m6_9 <- dplyr::filter(runN, gender == "MALE", age < 10)
run_f10_14 <- dplyr::filter(runN, gender == "FEMALE", age < 15, age >= 10)
run_m10_14 <- dplyr::filter(runN, gender == "MALE", age < 15, age >= 10)
run_f15_18 <- dplyr::filter(runN, gender == "FEMALE", age >= 15)
run_m15_18 <- dplyr::filter(runN, gender == "MALE", age >= 15)
#Make the run dataframes into a list.
runs_list <- list(runN, run_f, run_m, run_f6_9, run_m6_9, run_f10_14, run_m10_14, run_f15_18, run_m15_18)
#Use apply to apply a user-defined function to each of the runs, that will calculate evrything we want it to.
runs_output <- lapply(runs_list, function(x) mxc_bmiind(x)) #LAtest updata changed the assignment operator from = to <-
runs_outputSD <- lapply(runs_list, function(x) mxc_bmiindsd(x))
#Append the runs_output to the dataframe.
mulruns[i, 1] = i
mulruns[i, c(2:145)] = as.data.frame(runs_output)
mulrunsSD[i, 1] = i
mulrunsSD[i, c(2:145)] = as.data.frame(runs_outputSD)
#Write the file. Change it to replace the original file to save space
write.csv(r_form, paste("mxc run_", run_number, ".csv", sep = ""))
}
#Create the summary dataframe and use that.
#Use apply to find the means along the columns for each of the individual parameters.
bmi_means = apply(mulruns[, c(2:145)], 2, mean)
bmi_stdev = apply(mulruns[, c(2:145)], 2, sd)
bmi_CI_L = apply(mulruns[, c(2:145)], 2, Rmisc::CI)[1,]
bmi_CI_U = apply(mulruns[, c(2:145)], 2, Rmisc::CI)[3,]
#Create the for loop to characterzie the aspects of hte CIS we are chaning.
ch <- c()
for (i in 1:9) {
ch2 <- c((((i-1)*16)+2), (((i-1)*16)+3), (((i-1)*16)+4), (((i-1)*16)+5), (((i-1)*16)+6), (((i-1)*16)+7))
ch <- c(ch, ch2)
}
#Correct the standard deviaitons
bmi_stdev[(ch - 1)] <- apply(mulrunsSD[,ch], 2, mean)
#Deal with the sds
plus_minus <- mxc_dealsdbmi(mulrunsSD, ch)
bmi_CI_L[(ch - 1)] = bmi_means[(ch - 1)] - plus_minus
bmi_CI_U[(ch - 1)] = bmi_means[(ch - 1)] + plus_minus
bmi_summary <- data.frame(bmi_means, bmi_stdev, bmi_CI_L, bmi_CI_U)
#Create the BMI format files.
#Make a Third file in a Final Format.
groups = 144
final_bmi <- data.frame(Gender = numeric(groups), Age = numeric(groups), Variable = numeric(groups), Timepoint = numeric(groups), Value = numeric(groups))
#fill the gender column
final_bmi$Gender[c(1:16)] = "All"
final_bmi$Gender[c(17:32, 49:64, 81:96, 113:128)] = "Female"
final_bmi$Gender[c(33:48, 65:80, 97:112, 129:144)] = "Male"
#Fill the age column.
final_bmi$Age[c(1:48)] = "All"
final_bmi$Age[c(49:80)] = "6 - 9.99yrs"
final_bmi$Age[c(81:112)] = "10 - 14.99yrs"
final_bmi$Age[c(113:144)] = "15 - 18.99yrs"
starts = c()
ends = c()
changes = c()
sizes = c()
#This was a complicated thing that i did not take the time to really explain in detail. This is meant to be able to place the
#start ends and change labels in hte ringht row numbers, so that foe each of htem there is a start end and a hcane in the correct
#order.
for (i in 1:9) {
starts = c(starts, ((i-1)*16) + 1)
starts = c(starts, ((i-1)*16) + 4)
starts = c(starts, ((i-1)*16) + 7)
starts = c(starts, ((i-1)*16) + 10)
starts = c(starts, ((i-1)*16) + 13)
ends = c(ends, ((i-1)*16)+2)
ends = c(ends, ((i-1)*16)+5)
ends = c(ends, ((i-1)*16)+8)
ends = c(ends, ((i-1)*16)+11)
ends = c(ends, ((i-1)*16)+14)
changes = c(changes, ((i-1)*16) + 3)
changes = c(changes, ((i-1)*16) + 6)
changes = c(changes, ((i-1)*16) + 9)
changes = c(changes, ((i-1)*16) + 12)
changes = c(changes, ((i-1)*16) + 15)
size = c(sizes, ((i - 1)*16) + 16)
}
#FIll in the timepoint
final_bmi$Timepoint[starts] = "Start"
final_bmi$Timepoint[ends] = "End"
final_bmi$Timepoint[changes] = "Change"
final_bmi$Timepoint[sizes] = "SampleSize"
#I could not find an easier way fo doing this, so i went fll brute.
bmis <- c()
pers <- c()
ovs <- c()
obs <- c()
owo <- c()
sams <- c()
for (i in 1:9) {
bmis <- c(bmis, c((((i - 1)*16) + 1), (((i - 1)*16) + 2), (((i - 1)*16) + 3)))
pers <- c(pers, c((((i - 1)*16) + 4), (((i - 1)*16) + 5), (((i - 1)*16) + 6)))
ovs <- c(ovs, c((((i - 1)*16) + 7), (((i - 1)*16) + 8), (((i - 1)*16) + 9)))
obs <- c(obs, c((((i - 1)*16) + 10), (((i - 1)*16) + 11), (((i - 1)*16) + 12)))
owo <- c(owo, c((((i - 1)*16) + 13), (((i - 1)*16) + 14), (((i - 1)*16) + 15)))
sams <- c(sams, c((((i - 1)*16) + 16)))
}
#Now the variable names
final_bmi$Variable[bmis] = "BMI"
final_bmi$Variable[pers] = "Percentile"
final_bmi$Variable[ovs] = "Overweight"
final_bmi$Variable[obs] = "Obese"
final_bmi$Variable[owo] = "OWO"
final_bmi$Variable[sams] = "Sample"
final_bmi$Value = bmi_means
final_perc <- dplyr::filter(final_bmi, Variable == "Percentile")
final_ow <- dplyr::filter(final_bmi, Variable == "Overweight")
final_ob <- dplyr::filter(final_bmi, Variable == "Obese")
final_bmi2 <- dplyr::filter(final_bmi, Variable == "BMI")
final_owo <- dplyr::filter(final_bmi, Variable == "OWO")
final_perc <- stats::reshape(final_perc, idvar = c("Gender", "Age"), v.names = "Value", drop = "Variable", timevar = "Timepoint", direction = "wide")
final_ow <- stats::reshape(final_ow, idvar = c("Gender", "Age"), timevar = "Timepoint", v.names = "Value", drop = "Variable", direction = "wide")
final_ob <- stats::reshape(final_ob, idvar = c("Gender", "Age"), timevar = "Timepoint", v.names = "Value", drop = "Variable", direction = "wide")
final_bmi2 <- stats::reshape(final_bmi2, idvar = c("Gender", "Age"), timevar = "Timepoint", v.names = "Value", drop = "Variable", direction = "wide")
final_owo <- stats::reshape(final_owo, idvar = c("Gender", "Age"), timevar = "Timepoint", v.names = "Value", drop = "Variable", direction = "wide")
all_finals <- cbind(final_bmi2, final_perc, final_ow, final_ob, final_owo)
write.csv(mulruns, "BMI_Individual Runs.csv")
write.csv(bmi_summary, "BMI Summary.csv")
write.csv(final_perc, "BMI Percentiles.csv")
write.csv(final_bmi2, "BMI Means.csv")
write.csv(final_ow, "Overweight.csv")
write.csv(final_ob, "Obese.csv")
write.csv(final_owo, "OWO.csv")
write.csv(all_finals, "Final All.csv")
on.exit(setwd(home))
print("BMI Processing is complete. Proceeding to next step.")
}
SindisoNyathi/GOPCMxC documentation built on May 10, 2019, 9:28 a.m.
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#' @title MxC BMI Function
#' @author Sindiso Nyathi
#' @description This function will run the BMI analysis portions of the Mexico Analysis.
#' @param home Parent directory path.
#' @param filename String name of file with the runs eg. "Baseline"
#' @return Will write multiple csv files into the Folders with the experiments.
#' @details This function will read in the folder with the runs, and read in each run. Then
#' call mxc_bmiind which will find the numbers/percentages of people OWO for each age and gender
#' grouping we are interested in.
#'mxc_bmi()
#'
#'@seealso {\code{\link{mxc_master}}, \code{\link{mxc_bmiind}}}
#'@examples
#'mxc_bmi(home, "Baseline")
#'mxc_bmi(home, "Intervention 1")
#'@family
#'
#' @export
mxc_bmi <- function(home, filename) {
#Set the Working directory to input folder.
setwd(paste(home, filename, "/", sep = ""))
#Set the constants. Run is the number of runs in the folder.
run = length(list.files(pattern = ".csv$"))
sim = 5 #In years.
#Create the dataframe that you will store the results in.
#This first one stores the raw results for each of the N runs.
mulruns <- data.frame(RunNo. = numeric(run),
#Overall
"Overall. BMI Mean Start" = numeric(run), "Overall. BMI Mean End" = numeric(run), "Overall. BMI Change" = numeric(run),
"Overall. Perc Mean Start" = numeric(run), "Overall. Perc Mean End" = numeric(run), "Overall. Perc Change" = numeric(run),
"Overall. Prop OW Start" = numeric(run), "Overall. Prop OW End" = numeric(run), "Overall. Prop OW Change" = numeric(run),
"Overall. Prop OB Start" = numeric(run), "Overall. Prop OB End" = numeric(run), "Overall. Prop OB Change" = numeric(run),
"Overall. Prop OWO Start" = numeric(run), "Overall. Prop OWO End" = numeric(run), "Overall. Prop OWO Change" = numeric(run),
"Overall. Sample Size" = numeric(run),
#Female
"F BMI Mean Start" = numeric(run), "F BMI Mean End" = numeric(run), "F BMI Change" = numeric(run),
"F Perc Mean Start" = numeric(run), "F Perc Mean End" = numeric(run), "F Perc Change" = numeric(run),
"F Prop OW Start" = numeric(run), "F Prop OW End" = numeric(run), "F Prop OW Change" = numeric(run),
"F Prop OB Start" = numeric(run), "F Prop OB End" = numeric(run), "F Prop OB Change" = numeric(run),
"F Prop OWO Start" = numeric(run), "F Prop OWO End" = numeric(run), "F Prop OWO Change" = numeric(run),
"F Sample Size" = numeric(run),
#Male
"M BMI Mean Start" = numeric(run), "M BMI Mean End" = numeric(run), "M BMI Change" = numeric(run),
"M Perc Mean Start" = numeric(run), "M Perc Mean End" = numeric(run), "M Perc Change" = numeric(run),
"M Prop OW Start" = numeric(run), "M Prop OW End" = numeric(run), "M Prop OW Change" = numeric(run),
"M Prop OB Start" = numeric(run), "M Prop OB End" = numeric(run), "M Prop OB Change" = numeric(run),
"M Prop OWO Start" = numeric(run), "M Prop OWO End" = numeric(run), "M Prop OWO Change" = numeric(run),
"M Sample Size" = numeric(run),
#Females, 6 - 9
"F 6-9. BMI Mean Start" = numeric(run), "F 6-9. BMI Mean End" = numeric(run), "F 6-9. BMI Change" = numeric(run),
"F 6-9. Perc Mean Start" = numeric(run), "F 6-9. Perc Mean End" = numeric(run), "F 6-9. Perc Change" = numeric(run),
"F 6-9. Prop OW Start" = numeric(run), "F 6-9. Prop OW End" = numeric(run), "F 6-9. Prop OW Change" = numeric(run),
"F 6-9. Prop OB Start" = numeric(run), "F 6-9. Prop OB End" = numeric(run), "F 6-9. Prop OB Change" = numeric(run),
"F 6-9. Prop OWO Start" = numeric(run), "F 6-9. Prop OWO End" = numeric(run), "F 6-9. Prop OWO Change" = numeric(run),
"F 6-9. Sample Size" = numeric(run),
#Males, 6 - 9
"M 6-9. BMI Mean Start" = numeric(run), "M 6-9. BMI Mean End" = numeric(run), "F 6-9. BMI Change" = numeric(run),
"M 6-9. Perc Mean Start" = numeric(run), "M 6-9. Perc Mean End" = numeric(run), "F 6-9. Perc Change" = numeric(run),
"M 6-9. Prop OW Start" = numeric(run), "M 6-9. Prop OW End" = numeric(run), "M 6-9. Prop OW Change" = numeric(run),
"M 6-9. Prop OB Start" = numeric(run), "M 6-9. Prop OB End" = numeric(run), "M 6-9. Prop OB Change" = numeric(run),
"M 6-9. Prop OWO Start" = numeric(run), "M 6-9. Prop OWO End" = numeric(run), "M 6-9. Prop OWO Change" = numeric(run),
"M 6-9. Sample Size" = numeric(run),
#Females 10 - 14
"F 10-14. BMI Mean Start" = numeric(run), "F 10-14. BMI Mean End" = numeric(run), "F 10-14. BMI Change" = numeric(run),
"F 10-14. Perc Mean Start" = numeric(run), "F 10-14. Perc Mean End" = numeric(run), "F 10-14. Perc Change" = numeric(run),
"F 10-14. Prop OW Start" = numeric(run), "F 10-14. Prop OW End" = numeric(run), "F 10-14. Prop OW Change" = numeric(run),
"F 10-14. Prop OB Start" = numeric(run), "F 10-14. Prop OB End" = numeric(run), "F 10-14. Prop OB Change" = numeric(run),
"F 10-14. Prop OWO Start" = numeric(run), "F 10-14. Prop OWO End" = numeric(run), "F 10-14. Prop OWO Change" = numeric(run),
"F 10-14. Sample Size" = numeric(run),
#Male 10 - 14
"M 10-14. BMI Mean Start" = numeric(run), "M 10-14. BMI Mean End" = numeric(run), "M 10-14. BMI Change" = numeric(run),
"M 10-14. Perc Mean Start" = numeric(run), "M 10-14. Perc Mean End" = numeric(run), "M 10-14. Perc Change" = numeric(run),
"M 10-14. Prop OW Start" = numeric(run), "M 10-14. Prop OW End" = numeric(run), "M 10-14. Prop OW Change" = numeric(run),
"M 10-14. Prop OB Start" = numeric(run), "M 10-14. Prop OB End" = numeric(run), "M 10-14. Prop OB Change" = numeric(run),
"M 10-14. Prop OWO Start" = numeric(run), "M 10-14. Prop OWO End" = numeric(run), "M 10-14. Prop OWO Change" = numeric(run),
"M 10-14. Sample Size" = numeric(run),
#Female 15 - 18
"F 15-18. BMI Mean Start" = numeric(run), "F 15-18. BMI Mean End" = numeric(run), "F 15-18. BMI Change" = numeric(run),
"F 15-18. Perc Mean Start" = numeric(run), "F 15-18. Perc Mean End" = numeric(run), "F 15-18. Perc Change" = numeric(run),
"F 15-18. Prop OW Start" = numeric(run), "F 15-18. Prop OW End" = numeric(run), "F 15-18. Prop OW Change" = numeric(run),
"F 15-18. Prop OB Start" = numeric(run), "F 15-18. Prop OB End" = numeric(run), "F 15-18. Prop OB Change" = numeric(run),
"F 15-18. Prop OWO Start" = numeric(run), "F 15-18. Prop OWO End" = numeric(run), "F 15-18. Prop OWO Change" = numeric(run),
"F 15-18. Sample Size" = numeric(run),
#Male 15 - 18
"M 15-18. BMI Mean Start" = numeric(run), "M 15-18. BMI Mean End" = numeric(run), "M 15-18. BMI Change" = numeric(run),
"M 15-18. Perc Mean Start" = numeric(run), "M 15-18. Perc Mean End" = numeric(run), "M 15-18. Perc Change" = numeric(run),
"M 15-18. Prop OW Start" = numeric(run), "M 15-18. Prop OW End" = numeric(run), "M 15-18. Prop OW Change" = numeric(run),
"M 15-18. Prop OB Start" = numeric(run), "M 15-18. Prop OB End" = numeric(run), "M 15-18. Prop OB Change" = numeric(run),
"M 15-18. Prop OWO Start" = numeric(run), "M 15-18. Prop OWO End" = numeric(run), "M 15-18. Prop OWO Change" = numeric(run),
"M 15-18. Sample Size" = numeric(run)
)
mulrunsSD <- data.frame(RunNo. = numeric(run),
#Overall
"Overall. BMI Mean Start" = numeric(run), "Overall. BMI Mean End" = numeric(run), "Overall. BMI Change" = numeric(run),
"Overall. Perc Mean Start" = numeric(run), "Overall. Perc Mean End" = numeric(run), "Overall. Perc Change" = numeric(run),
"Overall. Prop OW Start" = numeric(run), "Overall. Prop OW End" = numeric(run), "Overall. Prop OW Change" = numeric(run),
"Overall. Prop OB Start" = numeric(run), "Overall. Prop OB End" = numeric(run), "Overall. Prop OB Change" = numeric(run),
"Overall. Prop OWO Start" = numeric(run), "Overall. Prop OWO End" = numeric(run), "Overall. Prop OWO Change" = numeric(run),
"Overall. Sample Size" = numeric(run),
#Female
"F BMI Mean Start" = numeric(run), "F BMI Mean End" = numeric(run), "F BMI Change" = numeric(run),
"F Perc Mean Start" = numeric(run), "F Perc Mean End" = numeric(run), "F Perc Change" = numeric(run),
"F Prop OW Start" = numeric(run), "F Prop OW End" = numeric(run), "F Prop OW Change" = numeric(run),
"F Prop OB Start" = numeric(run), "F Prop OB End" = numeric(run), "F Prop OB Change" = numeric(run),
"F Prop OWO Start" = numeric(run), "F Prop OWO End" = numeric(run), "F Prop OWO Change" = numeric(run),
"F Sample Size" = numeric(run),
#Male
"M BMI Mean Start" = numeric(run), "M BMI Mean End" = numeric(run), "M BMI Change" = numeric(run),
"M Perc Mean Start" = numeric(run), "M Perc Mean End" = numeric(run), "M Perc Change" = numeric(run),
"M Prop OW Start" = numeric(run), "M Prop OW End" = numeric(run), "M Prop OW Change" = numeric(run),
"M Prop OB Start" = numeric(run), "M Prop OB End" = numeric(run), "M Prop OB Change" = numeric(run),
"M Prop OWO Start" = numeric(run), "M Prop OWO End" = numeric(run), "M Prop OWO Change" = numeric(run),
"M Sample Size" = numeric(run),
#Females, 6 - 9
"F 6-9. BMI Mean Start" = numeric(run), "F 6-9. BMI Mean End" = numeric(run), "F 6-9. BMI Change" = numeric(run),
"F 6-9. Perc Mean Start" = numeric(run), "F 6-9. Perc Mean End" = numeric(run), "F 6-9. Perc Change" = numeric(run),
"F 6-9. Prop OW Start" = numeric(run), "F 6-9. Prop OW End" = numeric(run), "F 6-9. Prop OW Change" = numeric(run),
"F 6-9. Prop OB Start" = numeric(run), "F 6-9. Prop OB End" = numeric(run), "F 6-9. Prop OB Change" = numeric(run),
"F 6-9. Prop OWO Start" = numeric(run), "F 6-9. Prop OWO End" = numeric(run), "F 6-9. Prop OWO Change" = numeric(run),
"F 6-9. Sample Size" = numeric(run),
#Males, 6 - 9
"M 6-9. BMI Mean Start" = numeric(run), "M 6-9. BMI Mean End" = numeric(run), "F 6-9. BMI Change" = numeric(run),
"M 6-9. Perc Mean Start" = numeric(run), "M 6-9. Perc Mean End" = numeric(run), "F 6-9. Perc Change" = numeric(run),
"M 6-9. Prop OW Start" = numeric(run), "M 6-9. Prop OW End" = numeric(run), "M 6-9. Prop OW Change" = numeric(run),
"M 6-9. Prop OB Start" = numeric(run), "M 6-9. Prop OB End" = numeric(run), "M 6-9. Prop OB Change" = numeric(run),
"M 6-9. Prop OWO Start" = numeric(run), "M 6-9. Prop OWO End" = numeric(run), "M 6-9. Prop OWO Change" = numeric(run),
"M 6-9. Sample Size" = numeric(run),
#Females 10 - 14
"F 10-14. BMI Mean Start" = numeric(run), "F 10-14. BMI Mean End" = numeric(run), "F 10-14. BMI Change" = numeric(run),
"F 10-14. Perc Mean Start" = numeric(run), "F 10-14. Perc Mean End" = numeric(run), "F 10-14. Perc Change" = numeric(run),
"F 10-14. Prop OW Start" = numeric(run), "F 10-14. Prop OW End" = numeric(run), "F 10-14. Prop OW Change" = numeric(run),
"F 10-14. Prop OB Start" = numeric(run), "F 10-14. Prop OB End" = numeric(run), "F 10-14. Prop OB Change" = numeric(run),
"F 10-14. Prop OWO Start" = numeric(run), "F 10-14. Prop OWO End" = numeric(run), "F 10-14. Prop OWO Change" = numeric(run),
"F 10-14. Sample Size" = numeric(run),
#Male 10 - 14
"M 10-14. BMI Mean Start" = numeric(run), "M 10-14. BMI Mean End" = numeric(run), "M 10-14. BMI Change" = numeric(run),
"M 10-14. Perc Mean Start" = numeric(run), "M 10-14. Perc Mean End" = numeric(run), "M 10-14. Perc Change" = numeric(run),
"M 10-14. Prop OW Start" = numeric(run), "M 10-14. Prop OW End" = numeric(run), "M 10-14. Prop OW Change" = numeric(run),
"M 10-14. Prop OB Start" = numeric(run), "M 10-14. Prop OB End" = numeric(run), "M 10-14. Prop OB Change" = numeric(run),
"M 10-14. Prop OWO Start" = numeric(run), "M 10-14. Prop OWO End" = numeric(run), "M 10-14. Prop OWO Change" = numeric(run),
"M 10-14. Sample Size" = numeric(run),
#Female 15 - 18
"F 15-18. BMI Mean Start" = numeric(run), "F 15-18. BMI Mean End" = numeric(run), "F 15-18. BMI Change" = numeric(run),
"F 15-18. Perc Mean Start" = numeric(run), "F 15-18. Perc Mean End" = numeric(run), "F 15-18. Perc Change" = numeric(run),
"F 15-18. Prop OW Start" = numeric(run), "F 15-18. Prop OW End" = numeric(run), "F 15-18. Prop OW Change" = numeric(run),
"F 15-18. Prop OB Start" = numeric(run), "F 15-18. Prop OB End" = numeric(run), "F 15-18. Prop OB Change" = numeric(run),
"F 15-18. Prop OWO Start" = numeric(run), "F 15-18. Prop OWO End" = numeric(run), "F 15-18. Prop OWO Change" = numeric(run),
"F 15-18. Sample Size" = numeric(run),
#Male 15 - 18
"M 15-18. BMI Mean Start" = numeric(run), "M 15-18. BMI Mean End" = numeric(run), "M 15-18. BMI Change" = numeric(run),
"M 15-18. Perc Mean Start" = numeric(run), "M 15-18. Perc Mean End" = numeric(run), "M 15-18. Perc Change" = numeric(run),
"M 15-18. Prop OW Start" = numeric(run), "M 15-18. Prop OW End" = numeric(run), "M 15-18. Prop OW Change" = numeric(run),
"M 15-18. Prop OB Start" = numeric(run), "M 15-18. Prop OB End" = numeric(run), "M 15-18. Prop OB Change" = numeric(run),
"M 15-18. Prop OWO Start" = numeric(run), "M 15-18. Prop OWO End" = numeric(run), "M 15-18. Prop OWO Change" = numeric(run),
"M 15-18. Sample Size" = numeric(run)
)
#Use a for loop to iterate through all the runs.
for (i in 1:run) {
#read in a run, and process the BMI for that run
runN <- read.csv(paste("mxc run_", i, ".csv", sep = ""))
#Substract the age in the runs from the simulation length.
runN$age = runN$initial_age
#Change the column names for the runs.
runN["bmi_S"] <- runN$initial_bmi
runN["bmi_E"] <- runN$final_bmi
runN["perc_S"] <- runN$initial_bmi_percentile
runN["perc_E"] <- runN$final_bmi_percentile
#Columns for BMI/Percentile change.
runN["delta_bmi"] <- runN$bmi_E - runN$bmi_S
runN["delta_perc"] <- runN$perc_E - runN$perc_S
#Make the subrun files for each age and gender combo..
run_f <- dplyr::filter(runN, gender == "FEMALE")
run_m <- dplyr::filter(runN, gender == "MALE")
run_f6_9 <- dplyr::filter(runN, gender == "FEMALE", age < 10)
run_m6_9 <- dplyr::filter(runN, gender == "MALE", age < 10)
run_f10_14 <- dplyr::filter(runN, gender == "FEMALE", age < 15, age >= 10)
run_m10_14 <- dplyr::filter(runN, gender == "MALE", age < 15, age >= 10)
run_f15_18 <- dplyr::filter(runN, gender == "FEMALE", age >= 15)
run_m15_18 <- dplyr::filter(runN, gender == "MALE", age >= 15)
#Make the run dataframes into a list.
runs_list <- list(runN, run_f, run_m, run_f6_9, run_m6_9, run_f10_14, run_m10_14, run_f15_18, run_m15_18)
#Use apply to apply a user-defined function to each of the runs, that will calculate evrything we want it to.
runs_output <- lapply(runs_list, function(x) mxc_bmiind(x)) #LAtest updata changed the assignment operator from = to <-
runs_outputSD <- lapply(runs_list, function(x) mxc_bmiindsd(x))
#Append the runs_output to the dataframe.
mulruns[i, 1] = i
mulruns[i, c(2:145)] = as.data.frame(runs_output)
mulrunsSD[i, 1] = i
mulrunsSD[i, c(2:145)] = as.data.frame(runs_outputSD)
#Write the file. Change it to replace the original file to save space
write.csv(r_form, paste("mxc run_", run_number, ".csv", sep = ""))
}
#Create the summary dataframe and use that.
#Use apply to find the means along the columns for each of the individual parameters.
bmi_means = apply(mulruns[, c(2:145)], 2, mean)
bmi_stdev = apply(mulruns[, c(2:145)], 2, sd)
bmi_CI_L = apply(mulruns[, c(2:145)], 2, Rmisc::CI)[1,]
bmi_CI_U = apply(mulruns[, c(2:145)], 2, Rmisc::CI)[3,]
#Create the for loop to characterzie the aspects of hte CIS we are chaning.
ch <- c()
for (i in 1:9) {
ch2 <- c((((i-1)*16)+2), (((i-1)*16)+3), (((i-1)*16)+4), (((i-1)*16)+5), (((i-1)*16)+6), (((i-1)*16)+7))
ch <- c(ch, ch2)
}
#Correct the standard deviaitons
bmi_stdev[(ch - 1)] <- apply(mulrunsSD[,ch], 2, mean)
#Deal with the sds
plus_minus <- mxc_dealsdbmi(mulrunsSD, ch)
bmi_CI_L[(ch - 1)] = bmi_means[(ch - 1)] - plus_minus
bmi_CI_U[(ch - 1)] = bmi_means[(ch - 1)] + plus_minus
bmi_summary <- data.frame(bmi_means, bmi_stdev, bmi_CI_L, bmi_CI_U)
#Create the BMI format files.
#Make a Third file in a Final Format.
groups = 144
final_bmi <- data.frame(Gender = numeric(groups), Age = numeric(groups), Variable = numeric(groups), Timepoint = numeric(groups), Value = numeric(groups))
#fill the gender column
final_bmi$Gender[c(1:16)] = "All"
final_bmi$Gender[c(17:32, 49:64, 81:96, 113:128)] = "Female"
final_bmi$Gender[c(33:48, 65:80, 97:112, 129:144)] = "Male"
#Fill the age column.
final_bmi$Age[c(1:48)] = "All"
final_bmi$Age[c(49:80)] = "6 - 9.99yrs"
final_bmi$Age[c(81:112)] = "10 - 14.99yrs"
final_bmi$Age[c(113:144)] = "15 - 18.99yrs"
starts = c()
ends = c()
changes = c()
sizes = c()
#This was a complicated thing that i did not take the time to really explain in detail. This is meant to be able to place the
#start ends and change labels in hte ringht row numbers, so that foe each of htem there is a start end and a hcane in the correct
#order.
for (i in 1:9) {
starts = c(starts, ((i-1)*16) + 1)
starts = c(starts, ((i-1)*16) + 4)
starts = c(starts, ((i-1)*16) + 7)
starts = c(starts, ((i-1)*16) + 10)
starts = c(starts, ((i-1)*16) + 13)
ends = c(ends, ((i-1)*16)+2)
ends = c(ends, ((i-1)*16)+5)
ends = c(ends, ((i-1)*16)+8)
ends = c(ends, ((i-1)*16)+11)
ends = c(ends, ((i-1)*16)+14)
changes = c(changes, ((i-1)*16) + 3)
changes = c(changes, ((i-1)*16) + 6)
changes = c(changes, ((i-1)*16) + 9)
changes = c(changes, ((i-1)*16) + 12)
changes = c(changes, ((i-1)*16) + 15)
size = c(sizes, ((i - 1)*16) + 16)
}
#FIll in the timepoint
final_bmi$Timepoint[starts] = "Start"
final_bmi$Timepoint[ends] = "End"
final_bmi$Timepoint[changes] = "Change"
final_bmi$Timepoint[sizes] = "SampleSize"
#I could not find an easier way fo doing this, so i went fll brute.
bmis <- c()
pers <- c()
ovs <- c()
obs <- c()
owo <- c()
sams <- c()
for (i in 1:9) {
bmis <- c(bmis, c((((i - 1)*16) + 1), (((i - 1)*16) + 2), (((i - 1)*16) + 3)))
pers <- c(pers, c((((i - 1)*16) + 4), (((i - 1)*16) + 5), (((i - 1)*16) + 6)))
ovs <- c(ovs, c((((i - 1)*16) + 7), (((i - 1)*16) + 8), (((i - 1)*16) + 9)))
obs <- c(obs, c((((i - 1)*16) + 10), (((i - 1)*16) + 11), (((i - 1)*16) + 12)))
owo <- c(owo, c((((i - 1)*16) + 13), (((i - 1)*16) + 14), (((i - 1)*16) + 15)))
sams <- c(sams, c((((i - 1)*16) + 16)))
}
#Now the variable names
final_bmi$Variable[bmis] = "BMI"
final_bmi$Variable[pers] = "Percentile"
final_bmi$Variable[ovs] = "Overweight"
final_bmi$Variable[obs] = "Obese"
final_bmi$Variable[owo] = "OWO"
final_bmi$Variable[sams] = "Sample"
final_bmi$Value = bmi_means
final_perc <- dplyr::filter(final_bmi, Variable == "Percentile")
final_ow <- dplyr::filter(final_bmi, Variable == "Overweight")
final_ob <- dplyr::filter(final_bmi, Variable == "Obese")
final_bmi2 <- dplyr::filter(final_bmi, Variable == "BMI")
final_owo <- dplyr::filter(final_bmi, Variable == "OWO")
final_perc <- stats::reshape(final_perc, idvar = c("Gender", "Age"), v.names = "Value", drop = "Variable", timevar = "Timepoint", direction = "wide")
final_ow <- stats::reshape(final_ow, idvar = c("Gender", "Age"), timevar = "Timepoint", v.names = "Value", drop = "Variable", direction = "wide")
final_ob <- stats::reshape(final_ob, idvar = c("Gender", "Age"), timevar = "Timepoint", v.names = "Value", drop = "Variable", direction = "wide")
final_bmi2 <- stats::reshape(final_bmi2, idvar = c("Gender", "Age"), timevar = "Timepoint", v.names = "Value", drop = "Variable", direction = "wide")
final_owo <- stats::reshape(final_owo, idvar = c("Gender", "Age"), timevar = "Timepoint", v.names = "Value", drop = "Variable", direction = "wide")
all_finals <- cbind(final_bmi2, final_perc, final_ow, final_ob, final_owo)
write.csv(mulruns, "BMI_Individual Runs.csv")
write.csv(bmi_summary, "BMI Summary.csv")
write.csv(final_perc, "BMI Percentiles.csv")
write.csv(final_bmi2, "BMI Means.csv")
write.csv(final_ow, "Overweight.csv")
write.csv(final_ob, "Obese.csv")
write.csv(final_owo, "OWO.csv")
write.csv(all_finals, "Final All.csv")
on.exit(setwd(home))
print("BMI Processing is complete. Proceeding to next step.")
}
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