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drcfit <- function(data, chooseone=TRUE,
probit = TRUE, logit = FALSE, weibull = FALSE,
linlogit = FALSE, level = 0.95,
showED50 = FALSE,
EDx = NULL)
{
if(!is.null(data$ok)) data <- subset(data,ok!="no fit") # Don't use data
# with ok set to
# "no fit"
substances <- levels(data$substance)
ri <- rix <- 0 # ri is the index over the result rows
# rix is used later to check if any
# model result was appended
rsubstance <- array() # the substance names in the results
rndl <- vector() # number of dose levels
rn <- vector() # mean number of replicates
# in each dose level
runit <- vector() # vector of units for each result row
rlhd <- rlld <- vector() # highest and lowest doses tested
mtype <- array() # the modeltypes
sigma <- array() # the standard deviation of the residuals
logED50 <- vector()
logED50low <- logED50high <- vector()
a <- b <- c <- vector()
models <- list() # a list containing the dose-response models
splitted <- split(data,data$substance)
for (i in substances) {
tmp <- splitted[[i]]
fit <- FALSE
if (length(tmp) != 0) {
unit <- levels(as.factor(as.vector(tmp$unit)))
message("\n",i,": Fitting data...\n")
} else {
unit <- ""
message("\n",i,": No data\n")
}
if (length(unit) > 1) {
message("More than one unit for substance ",i,", halting\n\n")
break
}
if (length(tmp$response) == 0) {
nodata = TRUE
} else {
nodata = FALSE
}
rix <- ri
if (nodata) {
n <- ndl <- 0
} else {
ndl <- length(levels(factor(tmp$dose)))
n <- length(tmp$response)
highestdose <- max(tmp$dose)
lowestdose <- min(tmp$dose)
lhd <- log10(highestdose)
lld <- log10(lowestdose)
responseathighestdose <- mean(subset(tmp,dose==highestdose)$response)
responseatlowestdose <- mean(subset(tmp,dose==lowestdose)$response)
if (responseathighestdose < 0.5) {
inactive <- FALSE
if (responseatlowestdose < 0.5) {
active <- TRUE
} else {
active <- FALSE
if (linlogit)
{
m <- try(drm(response ~ dose, data = tmp, fct = BC.4(fixed = c(NA, 1, NA, NA))))
if (chooseone==FALSE || fit==FALSE) {
if (!inherits(m, "try-error")) {
fit <- TRUE
ri <- ri + 1
mtype[[ri]] <- "linlogit"
models[[ri]] <- m
s <- summary(m)
sigma[[ri]] <- s$rseMat[1, "rse"]
rsubstance[[ri]] <- i
rndl[[ri]] <- ndl
rn[[ri]] <- n
runit[[ri]] <- unit
rlld[[ri]] <- log10(lowestdose)
rlhd[[ri]] <- log10(highestdose)
ED50 <- try(ED(m, 50, interval = "delta", display = FALSE))
if (!inherits(ED50, "try-error")) {
logED50[[ri]] <- log10(ED50["1:50", "Estimate"])
logED50low[[ri]] <- log10(ED50["1:50", "Lower"])
logED50high[[ri]] <- log10(ED50["1:50", "Upper"])
if (logED50[[ri]] > rlhd[[ri]]) {
mtype[[ri]] <- "no fit"
logED50[[ri]] <- NA
logED50low[[ri]] <- NA
logED50high[[ri]] <- NA
}
} else {
mtype[[ri]] <- "no ED50"
}
a[[ri]] <- coef(m)[[2]]
b[[ri]] <- coef(m)[[1]]
c[[ri]] <- coef(m)[[3]]
}
}
}
if (probit)
{
m <- try(drm(response ~ dose, data = tmp,
fct = LN.2()))
if (chooseone==FALSE || fit==FALSE) {
if (!inherits(m, "try-error")) {
fit <- TRUE
ri <- ri + 1
models[[ri]] <- m
s <- summary(m)
sigma[[ri]] <- s$rseMat[1, "rse"]
rsubstance[[ri]] <- i
rndl[[ri]] <- ndl
rn[[ri]] <- n
runit[[ri]] <- unit
rlld[[ri]] <- log10(lowestdose)
rlhd[[ri]] <- log10(highestdose)
logED50[[ri]] <- log10(coef(m)[[2]])
c[[ri]] <- NA
if (logED50[[ri]] > rlhd[[ri]]) {
mtype[[ri]] <- "no fit"
logED50[[ri]] <- NA
logED50low[[ri]] <- NA
logED50high[[ri]] <- NA
a[[ri]] <- NA
b[[ri]] <- NA
} else {
mtype[[ri]] <- "probit"
ED50 <- ED(m, 50, interval = "delta", display = FALSE)
logED50low[[ri]] <- log10(ED50["1:50", "Lower"])
logED50high[[ri]] <- log10(ED50["1:50", "Upper"])
a[[ri]] <- coef(m)[[2]]
b[[ri]] <- coef(m)[[1]]
}
}
}
}
if (logit)
{
m <- try(drm(response ~ dose, data = tmp, fct = LL.2()))
if (chooseone==FALSE || fit==FALSE) {
if (!inherits(m, "try-error")) {
fit <- TRUE
ri <- ri + 1
models[[ri]] <- m
s <- summary(m)
sigma[[ri]] <- s$rseMat[1, "rse"]
rsubstance[[ri]] <- i
rndl[[ri]] <- ndl
rn[[ri]] <- n
runit[[ri]] <- unit
rlld[[ri]] <- log10(lowestdose)
rlhd[[ri]] <- log10(highestdose)
logED50[[ri]] <- log10(coef(m)[[2]])
c[[ri]] <- NA
if (logED50[[ri]] > rlhd[[ri]]) {
mtype[[ri]] <- "no fit"
logED50[[ri]] <- NA
logED50low[[ri]] <- NA
logED50high[[ri]] <- NA
a[[ri]] <- NA
b[[ri]] <- NA
} else {
mtype[[ri]] <- "logit"
ED50 <- ED(m, 50, interval = "delta", display = FALSE)
logED50low[[ri]] <- log10(ED50["1:50", "Lower"])
logED50high[[ri]] <- log10(ED50["1:50", "Upper"])
a[[ri]] <- coef(m)[[2]]
b[[ri]] <- coef(m)[[1]]
}
}
}
}
if (weibull)
{
m <- try(drm(response ~ dose, data = tmp, fct = W1.2()))
if (chooseone==FALSE || fit==FALSE) {
if (!inherits(m, "try-error")) {
fit <- TRUE
ri <- ri + 1
models[[ri]] <- m
s <- summary(m)
sigma[[ri]] <- s$rseMat[1, "rse"]
rsubstance[[ri]] <- i
rndl[[ri]] <- ndl
rn[[ri]] <- n
runit[[ri]] <- unit
rlld[[ri]] <- log10(lowestdose)
rlhd[[ri]] <- log10(highestdose)
c[[ri]] <- NA
ED50 <- ED(m, 50, interval = "delta", display = FALSE)
logED50[[ri]] <- log10(ED50["1:50", "Estimate"])
if (logED50[[ri]] > rlhd[[ri]]) {
mtype[[ri]] <- "no fit"
logED50[[ri]] <- NA
logED50low[[ri]] <- NA
logED50high[[ri]] <- NA
a[[ri]] <- NA
b[[ri]] <- NA
} else {
mtype[[ri]] <- "weibull"
logED50low[[ri]] <- log10(ED50["1:50", "Lower"])
logED50high[[ri]] <- log10(ED50["1:50", "Upper"])
a[[ri]] <- logED50[[ri]]
b[[ri]] <- coef(m)[[1]]
}
}
}
}
}
} else {
inactive <- TRUE
}
}
if (ri == rix) { # if no entry was appended for this substance
ri <- ri + 1
rsubstance[[ri]] <- i
rndl[[ri]] <- ndl
rn[[ri]] <- n
if (nodata) {
rlld[[ri]] <- rlhd[[i]] <- NA
mtype[[ri]] <- "no data"
runit[[ri]] <- NA
} else {
rlld[[ri]] <- log10(lowestdose)
rlhd[[i]] <- log10(highestdose)
runit[[ri]] <- unit
if (inactive) {
mtype[[ri]] <- "inactive"
} else {
if (active) {
mtype[[ri]] <- "active"
} else {
mtype[[ri]] <- "no fit"
}
}
}
sigma[[ri]] <- NA
logED50[[ri]] <- NA
logED50low[[ri]] <- NA
logED50high[[ri]] <- NA
a[[ri]] <- NA
b[[ri]] <- NA
c[[ri]] <- NA
}
}
results <- data.frame(rsubstance, rndl, rn, rlld, rlhd, mtype,
logED50, logED50low, logED50high, runit, sigma, a, b)
lower_level_percent = paste(100 * (1 - level)/2, "%", sep = "")
upper_level_percent = paste(100 * (1 + level)/2, "%", sep = "")
names(results) <- c("Substance","ndl","n","lld","lhd","mtype","logED50",
lower_level_percent, upper_level_percent,
"unit","sigma","a","b")
if (linlogit) {
results$c <- c
}
if (showED50) {
results[c("ED50", paste("ED50", c(lower_level_percent, upper_level_percent)))] <-
10^results[7:9]
}
if (!is.null(EDx)) {
for (row.i in 1:ri) {
m <- models[[row.i]]
mtype <- as.character(results[row.i, "mtype"])
if (mtype %in% c("probit", "logit", "weibull", "linlogit")) {
for (EDi in EDx) {
EDx.drc = try(ED(m, EDi, interval = "delta", display = FALSE, level = level))
if (!inherits(EDx.drc, "try-error")) {
results[row.i, paste0("EDx", EDi)] <- EDx.drc[paste0("1:", EDi), "Estimate"]
results[row.i, paste0("EDx", EDi, " ", lower_level_percent)] <- EDx.drc[paste0("1:", EDi),
"Lower"]
results[row.i, paste0("EDx", EDi, " ", upper_level_percent)] <- EDx.drc[paste0("1:", EDi),
"Upper"]
}
}
}
}
}
attr(results, "models") <- models
return(results)
}
# vim: set ts=4 sw=4 expandtab:
|
