additional documentation and clarified code

R/Mods.R

@@ -311,8 +311,8 @@ plot.Mods <- function(x, nPoints = 200, superpose = FALSE, xlab = "Dose",
 }
 
 
-#' Calculate dose estimates for a fitted dose-response model (via \code{\link{fitMod}} or \code{\link{bFitMod}}) or a
-#' \code{\link{Mods}} object
+#' Calculate dose estimates for a fitted dose-response model (via \code{\link{fitMod}}, \code{\link{bFitMod}}) 
+#'  or \code{\link{maFitMod}}) or a \code{\link{Mods}} object
 #'
 #' @description The TD (target dose) is defined as the dose that achieves a target effect of Delta over placebo (if
 #' there are multiple such doses, the smallest is chosen):
@@ -348,7 +348,7 @@ plot.Mods <- function(x, nPoints = 200, superpose = FALSE, xlab = "Dose",
 #' @param direction Direction to be used in defining the TD. This depends on whether an increasing
 #' or decreasing of the response variable is beneficial. In case of ED calculation only needed for maFit objects.
 #' @param doses Dose levels to be used if \samp{TDtype} or \samp{EDtype} are
-#' equal to \samp{"discrete"}. Needs to include placebo, .
+#' equal to \samp{"discrete"}. Needs to include placebo, and may not exceed the dose range of the model(s) provided in \samp{object}.
 #'
 #' @return Returns the dose estimate
 #'
@@ -389,7 +389,8 @@ TD <- function(object, Delta, TDtype = c("continuous", "discrete"),
     scal <- attr(object, "scal")
     nodes <- attr(object, "doses")
     maxD <- max(attr(object, "doses"))
-    if(any(doses > maxD))
+    TDtype <- match.arg(TDtype)
+    if(TDtype == "discrete" & any(doses > maxD))
       stop("Doses provided may not exceed the observed dose range")
     ## loop through list
     for(nam in names(object)){
@@ -417,7 +418,8 @@ TD <- function(object, Delta, TDtype = c("continuous", "discrete"),
     nodes <- attr(object, "nodes")
     doseNam <- attr(object, "doseRespNam")[1]
     maxD <- max(attr(object,"data")[[doseNam]])
-    if(any(doses > maxD))
+    TDtype <- match.arg(TDtype)
+    if(TDtype == "discrete" & any(doses > maxD))
       stop("Doses provided may not exceed the observed dose range")
     if(attr(object, "placAdj")){
       par <- c(0, par)
@@ -435,7 +437,8 @@ TD <- function(object, Delta, TDtype = c("continuous", "discrete"),
     nodes <- attr(object, "nodes")
     doseNam <- attr(object, "doseRespNam")[1]
     maxD <- max(attr(object,"data")[[doseNam]])
-    if(any(doses > maxD))
+    TDtype <- match.arg(TDtype)
+    if(TDtype == "discrete" & any(doses > maxD))
       stop("Doses provided may not exceed the observed dose range")
     if(attr(object, "placAdj")){
       if(nam == "linInt")
@@ -456,7 +459,7 @@ TD <- function(object, Delta, TDtype = c("continuous", "discrete"),
     TDtype <- match.arg(TDtype)
     maxD <-  max(object$args$dose)
     if(TDtype == "discrete"){
-      if(missing(doses))
+      if(is.null(doses))
         stop("For TDtype = \"discrete\" need the possible doses in doses argument")
       if(doses[1] != 0)
         stop("need placebo dose for TD calculation")
@@ -560,7 +563,7 @@ ED <- function(object, p, EDtype = c("continuous", "discrete"),
     EDtype <- match.arg(EDtype)
     maxD <- max(object$args$dose)
     if(EDtype == "discrete"){
-      if(missing(doses))
+      if(is.null(doses))
         stop("For EDtype = \"discrete\" need the possible doses in doses argument")
       if(!any(doses == 0))
         stop("need placebo dose for ED calculation")
@@ -584,11 +587,12 @@ ED <- function(object, p, EDtype = c("continuous", "discrete"),
 
     difs <- (pred_med - pred_med[1])
     ind <- which(difs > p*max(difs))
-    if(EDtype == "discrete")
-      ind <- ind[ind <= length(doses)] ## only include doses that where initially included
+    if(length(ind) == 0)
+      return(NA)
 
-    if (length(ind)>0) {
-      return(min(doseSeq[ind]))
+    edose <- min(doseSeq[ind])
+    if (EDtype == "continuous" | edose %in% doses) {## don't return maxD if it was not in originally provided doses for discrete type
+      return(edose)
     } else {
       return(NA)
     }

R/Mods_helpers.R

@@ -605,11 +605,12 @@ calcED <- function(model, pars, p, maxD, EDtype = c("continuous", "discrete"),
     }
   }
   ind <- which(resp > p*maxResp)
-  if(EDtype == "discrete")
-    ind <- ind[ind <= length(doses)] ## only include doses that where initially included
+  if(length(ind) == 0)
+    return(NA)
 
-  if(length(ind) > 0){ ## ED does exist return smallest dose fulfilling threshold
-    return(min(doseSeq[ind]))
+  edose <- min(doseSeq[ind])
+  if (EDtype == "continuous" | edose %in% doses) {## don't return maxD if it was not in originally provided doses for discrete type
+    return(edose)
   } else {
     return(NA)
   }

R/maFitMod.R

@@ -110,8 +110,8 @@ maFitMod <- function(dose, resp, S, models,
 #' @param doseSeq Where to calculate predictions. 
 #' @param ... Further arguments (currently ignored)
 #' @rdname maFitMod
-#' @method predict maFitMod
-#' #' @export
+#' @method predict maFit
+#' @export
 predict.maFit <- function(object,
                           summaryFct = function(x) quantile(x, probs = c(0.025, 0.25, 0.5, 0.75, 0.975)),
                           doseSeq = NULL,