diff options
Diffstat (limited to 'R/drfit.R')
| -rw-r--r-- | R/drfit.R | 47 |
1 files changed, 20 insertions, 27 deletions
@@ -18,7 +18,7 @@ drfit <- function(data, startlogED50 = NA, chooseone=TRUE, # model result was appended rsubstance <- array() # the substance names in the results rndl <- vector() # number of dose levels - rn <- vector() # mean number of replicates + 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 @@ -75,13 +75,12 @@ drfit <- function(data, startlogED50 = NA, chooseone=TRUE, active <- TRUE } else { active <- FALSE - if (linlogit && + if (linlogit && length(subset(linlogitWrong,linlogitWrong == i))==0 && length(subset(allWrong,allWrong == i))==0) { m <- try(nls(response ~ linlogitf(dose,1,f,logED50,b), - data=tmp, algorithm="port", - start=list(f=f0,logED50=startlogED50[[i]],b=b0)), - silent = TRUE) + data=tmp, algorithm="port", + start=list(f=f0,logED50=startlogED50[[i]],b=b0))) if (!inherits(m, "try-error")) { fit <- TRUE ri <- ri + 1 @@ -105,8 +104,7 @@ drfit <- function(data, startlogED50 = NA, chooseone=TRUE, c[[ri]] <- NA } else { mtype[[ri]] <- "linlogit" - logED50conf <- try(confint(m,"logED50",level=level), - silent = TRUE) + logED50conf <- try(confint(m,"logED50",level=level)) if (!inherits(logED50conf, "try-error")) { logED50low[[ri]] <- logED50conf[[1]] logED50high[[ri]] <- logED50conf[[2]] @@ -124,9 +122,8 @@ drfit <- function(data, startlogED50 = NA, chooseone=TRUE, if (probit && length(subset(allWrong,allWrong == i))==0) { m <- try(nls(response ~ pnorm(-log10(dose),-logED50,scale), - data=tmp, algorithm="port", - start=list(logED50=startlogED50[[i]],scale=ps0)), - silent = TRUE) + data=tmp, algorithm="port", + start=list(logED50=startlogED50[[i]],scale=ps0))) if (chooseone==FALSE || fit==FALSE) { if (!inherits(m, "try-error")) { fit <- TRUE @@ -151,8 +148,7 @@ drfit <- function(data, startlogED50 = NA, chooseone=TRUE, b[[ri]] <- NA } else { mtype[[ri]] <- "probit" - logED50conf <- try(confint(m,"logED50",level=level), - silent = TRUE) + logED50conf <- try(confint(m,"logED50",level=level)) if (!inherits(logED50conf, "try-error")) { logED50low[[ri]] <- logED50conf[[1]] logED50high[[ri]] <- logED50conf[[2]] @@ -170,9 +166,8 @@ drfit <- function(data, startlogED50 = NA, chooseone=TRUE, if (logit && length(subset(allWrong,allWrong == i))==0) { m <- try(nls(response ~ plogis(-log10(dose),-logED50,scale), - data=tmp, algorithm="port", - start=list(logED50=startlogED50[[i]],scale=ls0)), - silent = TRUE) + data=tmp, algorithm="port", + start=list(logED50=startlogED50[[i]],scale=ls0))) if (chooseone==FALSE || fit==FALSE) { if (!inherits(m, "try-error")) { fit <- TRUE @@ -198,8 +193,7 @@ drfit <- function(data, startlogED50 = NA, chooseone=TRUE, b[[ri]] <- NA } else { mtype[[ri]] <- "logit" - logED50conf <- try(confint(m,"logED50",level=level), - silent = TRUE) + logED50conf <- try(confint(m,"logED50",level=level)) if (!inherits(logED50conf, "try-error")) { logED50low[[ri]] <- logED50conf[[1]] logED50high[[ri]] <- logED50conf[[2]] @@ -215,9 +209,8 @@ drfit <- function(data, startlogED50 = NA, chooseone=TRUE, if (weibull && length(subset(allWrong,allWrong == i))==0) { m <- try(nls(response ~ pweibull(-log10(dose)+location,shape), - data=tmp, algorithm="port", - start=list(location=startlogED50[[i]],shape=ws0)), - silent = TRUE) + data=tmp, algorithm="port", + start=list(location=startlogED50[[i]],shape=ws0))) if (chooseone==FALSE || fit==FALSE) { if (!inherits(m, "try-error")) { ri <- ri + 1 @@ -225,7 +218,7 @@ drfit <- function(data, startlogED50 = NA, chooseone=TRUE, a[[ri]] <- coef(m)[["location"]] b[[ri]] <- coef(m)[["shape"]] sqrdev <- function(logdose) { - (0.5 - pweibull( - logdose + a[[ri]], b[[ri]]))^2 + (0.5 - pweibull( - logdose + a[[ri]], b[[ri]]))^2 } logED50[[ri]] <- nlm(sqrdev,startlogED50[[i]])$estimate if (sqrdev(logED50[[ri]]) > 0.1) { @@ -298,7 +291,7 @@ drfit <- function(data, startlogED50 = NA, chooseone=TRUE, c[[ri]] <- NA } } - results <- data.frame(rsubstance, rndl, rn, rlld, rlhd, mtype, + results <- data.frame(rsubstance, rndl, rn, rlld, rlhd, mtype, logED50, logED50low, logED50high, runit, sigma, a, b) lower_level_percent = paste(100 * (1 - level)/2, "%", sep = "") upper_level_percent = paste(100 * (1 + level)/2, "%", sep = "") @@ -318,18 +311,18 @@ drfit <- function(data, startlogED50 = NA, chooseone=TRUE, if (mtype[[row.i]] %in% c("probit", "logit", "weibull", "linlogit")) { for (ED in EDx) { of <- function(x) { - abs(predict(models[[row.i]], data.frame(dose = 10^x)) - + abs(predict(models[[row.i]], data.frame(dose = 10^x)) - (1 - (ED/100))) - } - # Search over interval starting an order of magnitude below + } + # Search over interval starting an order of magnitude below # the lowest dose up to one order of magnitude above the # highest dose - o = optimize(of, + o = optimize(of, results[row.i, c("lld", "lhd")] + c(-1, 1)) # Only keep results within the tolerance if ((o$objective) < EDx.tolerance) { logdose.ED = o$minimum - results[row.i, paste0("EDx", ED)] <- 10^logdose.ED + results[row.i, paste0("EDx", ED)] <- 10^logdose.ED } } } |