diff options
| -rw-r--r-- | DESCRIPTION | 8 | ||||
| -rw-r--r-- | R/drfit.R | 97 | ||||
| -rw-r--r-- | man/drfit.Rd | 16 | ||||
| -rw-r--r-- | tests/IM1xIPC81.Rout.save | 41 | ||||
| -rw-r--r-- | tests/IM1xVibrio.Rout.save | 45 | ||||
| -rw-r--r-- | tests/XY.Rout.save | 18 | ||||
| -rw-r--r-- | tests/antifoul.Rout.save | 15 | ||||
| -rw-r--r-- | tests/pyrithione.Rout.save | 76 |
8 files changed, 181 insertions, 135 deletions
diff --git a/DESCRIPTION b/DESCRIPTION index 5d92da7..e12b6bf 100644 --- a/DESCRIPTION +++ b/DESCRIPTION @@ -1,14 +1,14 @@ Package: drfit -Version: 0.05-75 -Date: 2006-04-28 +Version: 0.05-76 +Date: 2006-05-04 Title: Dose-response data evaluation Author: Johannes Ranke <jranke@uni-bremen.de> Maintainer: Johannes Ranke <jranke@uni-bremen.de> -Depends: R (>= 2.1.0),stats,RODBC +Depends: R (>= 2.1.0),stats,MASS,RODBC Description: drfit provides basic and easy-to-use functions for fitting dose-response curves to dose-response data, calculating some (eco)toxicological parameters and plotting the results. Functions that are - fitted are the cumulative densitiy function of the lognormal distribution + fitted are the cumulative density function of the lognormal distribution (probit fit), of the logistic distribution (logit fit), of the weibull distribution (weibull fit) and a linear-logistic model ("linlogit" fit), derived from the latter, which is used to describe data showing stimulation @@ -1,27 +1,28 @@ drfit <- function(data, startlogED50 = NA, chooseone=TRUE, probit = TRUE, logit = FALSE, weibull = FALSE, - linlogit = FALSE, conf = FALSE, + linlogit = FALSE, level = 0.95, linlogitWrong = NA, allWrong = NA, s0 = 0.5, b0 = 2, f0 = 0) { - if(!is.null(data$ok)) data <- subset(data,ok!="no fit") # Don't use data with - # ok set to "no fit" + require(MASS) + if(!is.null(data$ok)) data <- subset(data,ok!="no fit") # Don't use data + # with ok set to + # "no fit" substances <- levels(data$substance) - ri <- rix <- 0 # ri is the index over the result rows - # rix is used later to check if any - # model result was appended - rsubstance <- array() # the substance names in the results - rndl <- vector() # number of dose levels - rn <- vector() # mean number of replicates - # in each dose level - runit <- vector() # vector of units for each result row - rlhd <- rlld <- vector() # highest and lowest doses tested - mtype <- array() # the modeltypes - sigma <- array() # the standard deviation of the residuals + ri <- rix <- 0 # ri is the index over the result rows + # rix is used later to check if any + # model result was appended + rsubstance <- array() # the substance names in the results + rndl <- vector() # number of dose levels + rn <- vector() # mean number of replicates + # in each dose level + runit <- vector() # vector of units for each result row + rlhd <- rlld <- vector() # highest and lowest doses tested + mtype <- array() # the modeltypes + sigma <- array() # the standard deviation of the residuals logED50 <- vector() - stderrlogED50 <- vector() - conflogED50 <- vector() + logED50low <- logED50high <- vector() a <- b <- c <- vector() splitted <- split(data,data$substance) @@ -87,15 +88,21 @@ drfit <- function(data, startlogED50 = NA, chooseone=TRUE, if (logED50[[ri]] > rlhd[[ri]]) { mtype[[ri]] <- "no fit" logED50[[ri]] <- NA - stderrlogED50[[ri]] <- NA - conflogED50[[ri]] <- NA + logED50low[[ri]] <- NA + logED50high[[ri]] <- NA a[[ri]] <- NA b[[ri]] <- NA c[[ri]] <- NA } else { mtype[[ri]] <- "linlogit" - stderrlogED50[[ri]] <- s$parameters["logED50","Std. Error"] - conflogED50[[ri]] <- stderrlogED50[[ri]] * qt(0.975, n - 3) + logED50conf <- try(confint(m,"logED50",level=level)) + if (!inherits(logED50conf, "try-error")) { + logED50low[[ri]] <- logED50conf[[1]] + logED50high[[ri]] <- logED50conf[[2]] + } else { + logED50low[[ri]] <- NA + logED50high[[ri]] <- NA + } a[[ri]] <- coef(m)[["logED50"]] b[[ri]] <- coef(m)[["b"]] c[[ri]] <- coef(m)[["f"]] @@ -125,14 +132,20 @@ drfit <- function(data, startlogED50 = NA, chooseone=TRUE, if (logED50[[ri]] > rlhd[[ri]]) { mtype[[ri]] <- "no fit" logED50[[ri]] <- NA - stderrlogED50[[ri]] <- NA - conflogED50[[ri]] <- NA + logED50low[[ri]] <- NA + logED50high[[ri]] <- NA a[[ri]] <- NA b[[ri]] <- NA } else { mtype[[ri]] <- "probit" - stderrlogED50[[ri]] <- s$parameters["logED50","Std. Error"] - conflogED50[[ri]] <- stderrlogED50[[ri]] * qt(0.975, n - 2) + logED50conf <- try(confint(m,"logED50",level=level)) + if (!inherits(logED50conf, "try-error")) { + logED50low[[ri]] <- logED50conf[[1]] + logED50high[[ri]] <- logED50conf[[2]] + } else { + logED50low[[ri]] <- NA + logED50high[[ri]] <- NA + } a[[ri]] <- coef(m)[["logED50"]] b[[ri]] <- coef(m)[["scale"]] } @@ -163,14 +176,20 @@ drfit <- function(data, startlogED50 = NA, chooseone=TRUE, if (logED50[[ri]] > rlhd[[ri]]) { mtype[[ri]] <- "no fit" logED50[[ri]] <- NA - stderrlogED50[[ri]] <- NA - conflogED50[[ri]] <- NA + logED50low[[ri]] <- NA + logED50high[[ri]] <- NA a[[ri]] <- NA b[[ri]] <- NA } else { mtype[[ri]] <- "logit" - stderrlogED50[[ri]] <- s$parameters["logED50","Std. Error"] - conflogED50[[ri]] <- stderrlogED50[[ri]] * qt(0.975, n - 2) + logED50conf <- try(confint(m,"logED50",level=level)) + if (!inherits(logED50conf, "try-error")) { + logED50low[[ri]] <- logED50conf[[1]] + logED50high[[ri]] <- logED50conf[[2]] + } else { + logED50low[[ri]] <- NA + logED50high[[ri]] <- NA + } } } } @@ -200,17 +219,15 @@ drfit <- function(data, startlogED50 = NA, chooseone=TRUE, } logED50[[ri]] <- nlm(sqrdev,startlogED50[[i]])$estimate c[[ri]] <- NA + logED50low[[ri]] <- NA + logED50high[[ri]] <- NA if (logED50[[ri]] > rlhd[[ri]]) { mtype[[ri]] <- "no fit" logED50[[ri]] <- NA - stderrlogED50[[ri]] <- NA - conflogED50[[ri]] <- NA a[[ri]] <- NA b[[ri]] <- NA } else { mtype[[ri]] <- "weibull" - stderrlogED50[[ri]] <- NA - conflogED50[[ri]] <- stderrlogED50[[ri]] * qt(0.975, n - 2) } } } @@ -247,21 +264,17 @@ drfit <- function(data, startlogED50 = NA, chooseone=TRUE, } sigma[[ri]] <- NA logED50[[ri]] <- NA - stderrlogED50[[ri]] <- NA - conflogED50[[ri]] <- NA + logED50low[[ri]] <- NA + logED50high[[ri]] <- NA a[[ri]] <- NA b[[ri]] <- NA c[[ri]] <- NA } } - if (conf) - { - results <- data.frame(rsubstance, rndl, rn, rlld, rlhd, mtype, logED50, conflogED50, runit, sigma, a, b) - names(results) <- c("Substance","ndl","n","lld","lhd","mtype","logED50","conf","unit","sigma","a","b") - } else { - results <- data.frame(rsubstance, rndl, rn, rlld, rlhd, mtype, logED50, stderrlogED50, runit, sigma, a, b) - names(results) <- c("Substance","ndl","n","lld","lhd","mtype","logED50","std","unit","sigma","a","b") - } + results <- data.frame(rsubstance, rndl, rn, rlld, rlhd, mtype, + logED50, logED50low, logED50high, runit, sigma, a, b) + names(results) <- c("Substance","ndl","n","lld","lhd","mtype", + "logED50",names(logED50conf)[[1]],names(logED50conf)[[2]],"unit","sigma","a","b") if (linlogit) { results$c <- c diff --git a/man/drfit.Rd b/man/drfit.Rd index a89b5dd..453c0f8 100644 --- a/man/drfit.Rd +++ b/man/drfit.Rd @@ -7,7 +7,7 @@ } \usage{ drfit(data, startlogED50 = NA, chooseone = TRUE, probit = TRUE, logit = FALSE, - weibull = FALSE, linlogit = FALSE, conf = FALSE, linlogitWrong = NA, + weibull = FALSE, linlogit = FALSE, level = 0.95, linlogitWrong = NA, allWrong = NA, s0 = 0.5, b0 = 2, f0 = 0) } \arguments{ @@ -43,10 +43,8 @@ A boolean defining if the linear-logistic function \code{\link{linlogitf}} as defined by van Ewijk and Hoekstra 1993 is fitted to the data. Default is FALSE.} - \item{conf}{ - A boolean defining if a confidence interval of the log ED50 is to be - listed for alpha = 5 \% (two-sided). If FALSE (default), the standard - deviation is listed in the output of drfit.} + \item{level}{ + The level for the confidence interval listed for the log ED50.} \item{linlogitWrong}{ An optional vector containing the names of the substances for which the linlogit function produces a wrong fit.} @@ -81,10 +79,10 @@ \code{lhd} is the decadic logarithm of the highest dose. For the \dQuote{linlogit}, \dQuote{logit} and \dQuote{probit} models, the parameter \code{a} that is reported coincides with the logED50, i.e the - logED50 is one of the model parameters that is being fitted, and - therefore, depending on the argument \code{conf}, a standard deviation - \code{std} or a confidence interval \code{conf} is reported for the - logED50. In the case of the \dQuote{weibull} model, \code{a} is a + logED50 is one of the model parameters that is being fitted. Therefore, + a confidence interval for the confidence level \code{level} is calculated + using the \code{\link[MASS:confint]{confint.nls}} function and listed. + In the case of the \dQuote{weibull} model, \code{a} is a location parameter. Parameter \code{b} in the case of the \dQuote{linlogit} fit is the variable b from the \code{\link{linlogitf}} function. In the case of \dQuote{probit} fit it is the standard deviation diff --git a/tests/IM1xIPC81.Rout.save b/tests/IM1xIPC81.Rout.save index b67ed2a..b56b8c9 100644 --- a/tests/IM1xIPC81.Rout.save +++ b/tests/IM1xIPC81.Rout.save @@ -16,6 +16,7 @@ Type 'demo()' for some demos, 'help()' for on-line help, or Type 'q()' to quit R. > library(drfit) +Loading required package: MASS Loading required package: RODBC > data(IM1xIPC81) > rIM1xIPC81 <- drfit(IM1xIPC81,linlogit=TRUE) @@ -35,41 +36,45 @@ IM15 BF4: Fitting data... IM16 BF4: Fitting data... IM17 BF4: Fitting data... +Waiting for profiling to be done... Error in numericDeriv(form[[3]], names(ind), env) : Missing value or an infinity produced when evaluating the model In addition: Warning message: NaNs produced in: pnorm(q, mean, sd, lower.tail, log.p) IM18 BF4: Fitting data... +Waiting for profiling to be done... Error in numericDeriv(form[[3]], names(ind), env) : Missing value or an infinity produced when evaluating the model In addition: Warning message: NaNs produced in: pnorm(q, mean, sd, lower.tail, log.p) IM19 BF4: Fitting data... +Waiting for profiling to be done... Error in numericDeriv(form[[3]], names(ind), env) : Missing value or an infinity produced when evaluating the model In addition: Warning message: NaNs produced in: pnorm(q, mean, sd, lower.tail, log.p) IM1-10 BF4: Fitting data... +Waiting for profiling to be done... > rIM1xIPC81 - Substance ndl n lld lhd mtype logED50 std unit -1 IM13 BF4 9 81 0.59176003 3.000000 inactive NA NA 然 -2 IM14 BF4 20 216 -0.01030017 3.176091 no fit NA NA 然 -3 IM15 BF4 9 135 0.59176003 3.000000 inactive NA NA 然 -4 IM16 BF4 9 108 0.59176003 3.000000 inactive NA NA 然 -5 IM17 BF4 9 81 0.59176003 3.000000 linlogit 2.5785719 0.03819482 然 -6 IM18 BF4 9 135 0.59176003 3.000000 linlogit 1.6806040 0.02982682 然 -7 IM19 BF4 9 81 0.59176003 3.000000 linlogit 1.6496121 0.02636274 然 -8 IM1-10 BF4 11 162 -0.01030017 3.000000 linlogit 0.7696961 0.04165397 然 - sigma a b c -1 NA NA NA NA -2 NA NA NA NA -3 NA NA NA NA -4 NA NA NA NA -5 0.2375857 2.5785719 2.300216 0.01468034 -6 0.2324871 1.6806040 2.237338 0.05719295 -7 0.1452716 1.6496121 1.976976 0.10956088 -8 0.2987708 0.7696961 1.936253 0.45808611 + Substance ndl n lld lhd mtype logED50 2.5% +1 IM13 BF4 9 81 0.59176003 3.000000 inactive NA NA +2 IM14 BF4 20 216 -0.01030017 3.176091 no fit NA NA +3 IM15 BF4 9 135 0.59176003 3.000000 inactive NA NA +4 IM16 BF4 9 108 0.59176003 3.000000 inactive NA NA +5 IM17 BF4 9 81 0.59176003 3.000000 linlogit 2.5785719 2.5057219 +6 IM18 BF4 9 135 0.59176003 3.000000 linlogit 1.6806040 1.6229756 +7 IM19 BF4 9 81 0.59176003 3.000000 linlogit 1.6496121 1.5984793 +8 IM1-10 BF4 11 162 -0.01030017 3.000000 linlogit 0.7696961 0.6870081 + 97.5% unit sigma a b c +1 NA 然 NA NA NA NA +2 NA 然 NA NA NA NA +3 NA 然 NA NA NA NA +4 NA 然 NA NA NA NA +5 2.6617385 然 0.2375857 2.5785719 2.300216 0.01468034 +6 1.7418917 然 0.2324871 1.6806040 2.237338 0.05719295 +7 1.7031463 然 0.1452716 1.6496121 1.976976 0.10956088 +8 0.8544213 然 0.2987708 0.7696961 1.936253 0.45808612 > diff --git a/tests/IM1xVibrio.Rout.save b/tests/IM1xVibrio.Rout.save index 5d37703..bebdcea 100644 --- a/tests/IM1xVibrio.Rout.save +++ b/tests/IM1xVibrio.Rout.save @@ -16,42 +16,51 @@ Type 'demo()' for some demos, 'help()' for on-line help, or Type 'q()' to quit R. > library(drfit) +Loading required package: MASS Loading required package: RODBC > data(IM1xVibrio) > rIM1xVibrio <- drfit(IM1xVibrio) IM13 BF4: Fitting data... +Waiting for profiling to be done... IM14 BF4: Fitting data... +Waiting for profiling to be done... IM15 BF4: Fitting data... +Waiting for profiling to be done... IM16 BF4: Fitting data... +Waiting for profiling to be done... IM17 BF4: Fitting data... +Waiting for profiling to be done... IM18 BF4: Fitting data... +Waiting for profiling to be done... IM19 BF4: Fitting data... +Waiting for profiling to be done... IM1-10 BF4: Fitting data... +Waiting for profiling to be done... > rIM1xVibrio - Substance ndl n lld lhd mtype logED50 std unit -1 IM13 BF4 13 22 -5.30103 4.69897 probit 3.9399128 0.03658457 然 -2 IM14 BF4 12 57 -4.30103 4.69897 probit 3.5442110 0.02060194 然 -3 IM15 BF4 7 20 -0.30103 4.69897 probit 3.1398488 0.01254468 然 -4 IM16 BF4 13 30 -4.30103 4.69897 probit 3.1804247 0.01801591 然 -5 IM17 BF4 10 20 -1.30103 4.69897 probit 2.4317301 0.03015341 然 -6 IM18 BF4 10 17 -2.30103 2.69897 probit 1.4015187 0.04053083 然 -7 IM19 BF4 13 22 -5.30103 2.69897 probit 0.7157942 0.02085130 然 -8 IM1-10 BF4 11 20 -6.30103 2.69897 probit -0.1790307 0.03623821 然 - sigma a b -1 0.06302893 3.9399128 0.5763074 -2 0.05905375 3.5442110 0.6561300 -3 0.02695476 3.1398488 0.5526675 -4 0.04514079 3.1804247 0.4881559 -5 0.04773317 2.4317301 0.6386547 -6 0.05611347 1.4015187 0.8008513 -7 0.02956284 0.7157942 0.6969275 -8 0.04098662 -0.1790307 0.8019351 + Substance ndl n lld lhd mtype logED50 2.5% 97.5% +1 IM13 BF4 13 22 -5.30103 4.69897 probit 3.9399128 3.8636215 4.0160099 +2 IM14 BF4 12 57 -4.30103 4.69897 probit 3.5442110 3.5030166 3.5855474 +3 IM15 BF4 7 20 -0.30103 4.69897 probit 3.1398488 3.1135935 3.1662394 +4 IM16 BF4 13 30 -4.30103 4.69897 probit 3.1804247 3.1435815 3.2176152 +5 IM17 BF4 10 20 -1.30103 4.69897 probit 2.4317301 2.3680656 2.4951179 +6 IM18 BF4 10 17 -2.30103 2.69897 probit 1.4015187 1.3146736 1.4880647 +7 IM19 BF4 13 22 -5.30103 2.69897 probit 0.7157942 0.6703743 0.7592458 +8 IM1-10 BF4 11 20 -6.30103 2.69897 probit -0.1790307 -0.2569430 -0.1037183 + unit sigma a b +1 然 0.06302893 3.9399128 0.5763074 +2 然 0.05905375 3.5442110 0.6561300 +3 然 0.02695476 3.1398488 0.5526675 +4 然 0.04514079 3.1804247 0.4881559 +5 然 0.04773317 2.4317301 0.6386547 +6 然 0.05611347 1.4015187 0.8008513 +7 然 0.02956284 0.7157942 0.6969275 +8 然 0.04098662 -0.1790307 0.8019351 > diff --git a/tests/XY.Rout.save b/tests/XY.Rout.save index 7bcc0df..d8098ae 100644 --- a/tests/XY.Rout.save +++ b/tests/XY.Rout.save @@ -16,6 +16,7 @@ Type 'demo()' for some demos, 'help()' for on-line help, or Type 'q()' to quit R. > library(drfit) +Loading required package: MASS Loading required package: RODBC > data(XY) > rXY <- drfit(XY) @@ -23,15 +24,16 @@ Loading required package: RODBC Control: Fitting data... Substance X: Fitting data... +Waiting for profiling to be done... Substance Y: Fitting data... > rXY - Substance ndl n lld lhd mtype logED50 std unit sigma -1 Control 1 6 -Inf -Inf inactive NA NA mg/L NA -2 Substance X 4 12 1 3 probit 2.161905 0.02425144 mg/L 0.04131746 -3 Substance Y 4 12 1 3 active NA NA mg/L NA - a b -1 NA NA -2 2.161905 0.5061306 -3 NA NA + Substance ndl n lld lhd mtype logED50 2.5% 97.5% unit +1 Control 1 6 -Inf -Inf inactive NA NA NA mg/L +2 Substance X 4 12 1 3 probit 2.161905 2.105861 2.214359 mg/L +3 Substance Y 4 12 1 3 active NA NA NA mg/L + sigma a b +1 NA NA NA +2 0.04131746 2.161905 0.5061306 +3 NA NA NA > diff --git a/tests/antifoul.Rout.save b/tests/antifoul.Rout.save index 5bc166c..9967240 100644 --- a/tests/antifoul.Rout.save +++ b/tests/antifoul.Rout.save @@ -16,18 +16,21 @@ Type 'demo()' for some demos, 'help()' for on-line help, or Type 'q()' to quit R. > library(drfit) +Loading required package: MASS Loading required package: RODBC > data(antifoul) > rantifoul <- drfit(antifoul) TBT: Fitting data... +Waiting for profiling to be done... Zn Pyrithion: Fitting data... +Waiting for profiling to be done... > rantifoul - Substance ndl n lld lhd mtype logED50 std unit -1 TBT 38 135 -2.709271 2.39794 probit -0.1643560 0.05349216 然 -2 Zn Pyrithion 27 81 -2.107210 2.00000 probit -0.3979222 0.05393693 然 - sigma a b -1 0.1928611 -0.1643560 0.6763882 -2 0.2286560 -0.3979222 0.4169632 + Substance ndl n lld lhd mtype logED50 2.5% +1 TBT 38 135 -2.709271 2.39794 probit -0.1643560 -0.2650411 +2 Zn Pyrithion 27 81 -2.107210 2.00000 probit -0.3979222 -0.5078291 + 97.5% unit sigma a b +1 -0.05648615 然 0.1928611 -0.1643560 0.6763882 +2 -0.29156056 然 0.2286560 -0.3979222 0.4169632 > diff --git a/tests/pyrithione.Rout.save b/tests/pyrithione.Rout.save index fb11ca9..2a05dd8 100644 --- a/tests/pyrithione.Rout.save +++ b/tests/pyrithione.Rout.save @@ -16,70 +16,86 @@ Type 'demo()' for some demos, 'help()' for on-line help, or Type 'q()' to quit R. > library(drfit) +Loading required package: MASS Loading required package: RODBC > data(pyrithione) > rpyr <- drfit(pyrithione,linlogit=TRUE,linlogitWrong=c("MSPT","MSPHI")) Na Pyrithion: Fitting data... +Waiting for profiling to be done... +Error in prof$getProfile() : number of iterations exceeded maximum of 50 Pyridin: Fitting data... PyNO: Fitting data... (PT)2: Fitting data... +Waiting for profiling to be done... MSO2P: Fitting data... MSPHI: Fitting data... +Waiting for profiling to be done... PyS: Fitting data... Error in nls(response ~ linlogitf(dose, 1, f, logED50, b), data = tmp, : step factor 0.000488281 reduced below 'minFactor' of 0.000976562 +Waiting for profiling to be done... +Error in numericDeriv(form[[3]], names(ind), env) : + Missing value or an infinity produced when evaluating the model +In addition: Warning message: +NaNs produced in: pnorm(q, mean, sd, lower.tail, log.p) Zn Pyrithion: Fitting data... +Waiting for profiling to be done... Cu Pyrithion: Fitting data... +Waiting for profiling to be done... Fe Pyrithion: Fitting data... +Waiting for profiling to be done... (PyS)2: Fitting data... Error in nls(response ~ linlogitf(dose, 1, f, logED50, b), data = tmp, : singular gradient +Waiting for profiling to be done... MSPT: Fitting data... +Waiting for profiling to be done... TBT: Fitting data... +Waiting for profiling to be done... NaJ: Fitting data... > rpyr - Substance ndl n lld lhd mtype logED50 std unit -1 Na Pyrithion 20 108 -2.107210 2.00000 linlogit -0.3461318 0.04237833 然 -2 Pyridin 19 161 0.591760 3.69897 inactive NA NA 然 -3 PyNO 19 81 0.591760 3.69897 no fit NA NA 然 -4 (PT)2 19 81 -2.408240 2.00000 linlogit -0.4197031 0.05030460 然 -5 MSO2P 28 108 -1.709271 3.69897 inactive NA NA 然 -6 MSPHI 19 81 0.591760 3.69897 probit 3.6625025 0.06724673 然 -7 PyS 18 80 -0.408240 3.00000 probit 2.6817944 0.02031252 然 -8 Zn Pyrithion 27 81 -2.107210 2.00000 linlogit -0.4132885 0.06234927 然 -9 Cu Pyrithion 19 79 -2.408240 2.00000 linlogit -0.3074717 0.07918130 然 -10 Fe Pyrithion 19 81 -2.408240 2.00000 linlogit -0.3534572 0.07263386 然 -11 (PyS)2 20 81 -0.408240 3.00000 probit 1.7840499 0.05230663 然 -12 MSPT 18 108 -0.408240 3.00000 probit 2.1384811 0.03379904 然 -13 TBT 38 135 -2.709271 2.39794 linlogit -0.1580954 0.05474371 然 -14 NaJ 10 108 0.591760 3.30103 inactive NA NA 然 - sigma a b c -1 0.20857751 -0.3461318 2.1188272 -0.26698979 -2 NA NA NA NA -3 0.09188853 NA NA NA -4 0.20509070 -0.4197031 1.8466994 -0.51508088 -5 NA NA NA NA -6 0.12943273 3.6625025 0.4387540 NA -7 0.13401920 2.6817944 0.1250523 NA -8 0.22877916 -0.4132885 1.7424846 0.61078660 -9 0.24494451 -0.3074717 1.0150649 -0.04897422 -10 0.23383185 -0.3534572 1.1823558 0.02510613 -11 0.23298721 1.7840499 0.4098018 NA -12 0.22881257 2.1384811 0.2112625 NA -13 0.19264079 -0.1580954 1.0406576 -0.02416104 -14 NA NA NA NA + Substance ndl n lld lhd mtype logED50 2.5% +1 Na Pyrithion 20 108 -2.107210 2.00000 linlogit -0.3461318 NA +2 Pyridin 19 161 0.591760 3.69897 inactive NA NA +3 PyNO 19 81 0.591760 3.69897 no fit NA NA +4 (PT)2 19 81 -2.408240 2.00000 linlogit -0.4197042 -0.5326102 +5 MSO2P 28 108 -1.709271 3.69897 inactive NA NA +6 MSPHI 19 81 0.591760 3.69897 probit 3.6625025 3.5548278 +7 PyS 18 80 -0.408240 3.00000 probit 2.6817944 NA +8 Zn Pyrithion 27 81 -2.107210 2.00000 linlogit -0.4132886 -0.5293327 +9 Cu Pyrithion 19 79 -2.408240 2.00000 linlogit -0.3074717 -0.4753489 +10 Fe Pyrithion 19 81 -2.408240 2.00000 linlogit -0.3534573 -0.5003829 +11 (PyS)2 20 81 -0.408240 3.00000 probit 1.7840499 1.6726792 +12 MSPT 18 108 -0.408240 3.00000 probit 2.1384811 2.0709306 +13 TBT 38 135 -2.709271 2.39794 linlogit -0.1580954 -0.2602139 +14 NaJ 10 108 0.591760 3.30103 inactive NA NA + 97.5% unit sigma a b c +1 NA 然 0.20857751 -0.3461318 2.1188275 -0.26698926 +2 NA 然 NA NA NA NA +3 NA 然 0.09188853 NA NA NA +4 NA 然 0.20509070 -0.4197042 1.8467290 -0.51505615 +5 NA 然 NA NA NA NA +6 3.88053203 然 0.12943273 3.6625025 0.4387540 NA +7 NA 然 0.13401920 2.6817944 0.1250523 NA +8 -0.29979846 然 0.22877916 -0.4132886 1.7424848 0.61079006 +9 -0.15442805 然 0.24494451 -0.3074717 1.0150650 -0.04897413 +10 -0.21459555 然 0.23383185 -0.3534573 1.1823561 0.02510663 +11 1.88824519 然 0.23298721 1.7840499 0.4098018 NA +12 2.20511512 然 0.22881257 2.1384811 0.2112625 NA +13 -0.05045493 然 0.19264079 -0.1580954 1.0406577 -0.02416082 +14 NA 然 NA NA NA NA > |