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) == 0) { unit <- NA } 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)$response) if (responseathighestdose < 0.5) { inactive <- FALSE if (responseatlowestdose < 0.5) { active <- TRUE } else { active <- FALSE if (linlogit) { m <- try(drm(response ~ dose, data = tmp, fct = BC.4(fixed = c(NA, 1, NA, NA))), silent = TRUE) if (chooseone==FALSE || fit==FALSE) { if (!inherits(m, "try-error")) { fit <- TRUE ri <- ri + 1 mtype[[ri]] <- "linlogit" models[[ri]] <- m s <- summary(m) sigma[[ri]] <- s$rseMat[1, "rse"] rsubstance[[ri]] <- i rndl[[ri]] <- ndl rn[[ri]] <- n runit[[ri]] <- unit rlld[[ri]] <- log10(lowestdose) rlhd[[ri]] <- log10(highestdose) logED50[[ri]] <- NA logED50low[[ri]] <- NA logED50high[[ri]] <- NA a[[ri]] <- coef(m)[[2]] b[[ri]] <- coef(m)[[1]] c[[ri]] <- coef(m)[[3]] ED50 <- try(ED(m, 50, interval = "delta", lower = lowestdose / 10, upper = highestdose * 10, display = FALSE), silent = TRUE) 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" } } } } } if (probit) { m <- try(drm(response ~ dose, data = tmp, fct = LN.2()), silent = TRUE) if (chooseone==FALSE || fit==FALSE) { if (!inherits(m, "try-error")) { fit <- TRUE ri <- ri + 1 models[[ri]] <- m s <- summary(m) sigma[[ri]] <- s$rseMat[1, "rse"] rsubstance[[ri]] <- i rndl[[ri]] <- ndl rn[[ri]] <- n runit[[ri]] <- unit rlld[[ri]] <- log10(lowestdose) rlhd[[ri]] <- log10(highestdose) logED50[[ri]] <- log10(coef(m)[[2]]) a[[ri]] <- coef(m)[[2]] b[[ri]] <- coef(m)[[1]] c[[ri]] <- NA if (logED50[[ri]] > rlhd[[ri]]) { mtype[[ri]] <- "no fit" logED50[[ri]] <- NA logED50low[[ri]] <- NA logED50high[[ri]] <- NA } else { mtype[[ri]] <- "probit" ED50 <- ED(m, 50, interval = "delta", display = FALSE) logED50low[[ri]] <- log10(ED50["1:50", "Lower"]) logED50high[[ri]] <- log10(ED50["1:50", "Upper"]) } } } } if (logit) { m <- try(drm(response ~ dose, data = tmp, fct = LL.2()), silent = TRUE) if (chooseone==FALSE || fit==FALSE) { if (!inherits(m, "try-error")) { fit <- TRUE ri <- ri + 1 models[[ri]] <- m s <- summary(m) sigma[[ri]] <- s$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]]) a[[ri]] <- coef(m)[[2]] b[[ri]] <- coef(m)[[1]] 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"]) } } } } if (weibull) { m <- try(drm(response ~ dose, data = tmp, fct = W1.2()), silent = TRUE) 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), silent = TRUE) 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: