fix several minor issues

NAMESPACE

@@ -44,7 +44,6 @@ S3method(plot, Mods)
 S3method(AIC, DRMod)
 S3method(gAIC, DRMod)
 S3method(logLik, DRMod)
-S3method(gAIC, DRMod)
 
 S3method(predict, bFitMod)
 S3method(plot, bFitMod)

R/DoseFinding-package.R

@@ -284,7 +284,6 @@ NULL
 #' @docType data
 #' @usage data(glycobrom)
 #' @format A data frame with 5 summary estimates (one per dose). Variables:
-#'   A data frame with 5 summary estimates (one per dose). Variables:
 #'  \describe{
 #'    \item{`dose`}{a numeric vector containing the dose values}
 #'    \item{`fev1`}{a numeric vector containing the least square
@@ -337,7 +336,7 @@ NULL
 #' @docType data
 #' @usage data(IBScovars)
 #' @format 
-#'   A data frame with 369 observations on the following 2 variables.
+#'   A data frame with 369 observations on the following 3 variables.
 #'   \describe{
 #'     \item{`gender`}{a factor specifying the gender}
 #'     \item{`dose`}{a numeric vector}
@@ -360,7 +359,7 @@ NULL
 #' @docType data
 #' @usage data(migraine)
 #' @format 
-#'  A data frame with 517 columns corresponding to the patients that
+#'  A data frame with 8 rows (one per dose group) summarizing 517 patients that
 #'  completed the trial
 #'  \describe{
 #'    \item{`dose`}{a numeric vector containing the dose values}

R/Mods_helpers.R

@@ -66,8 +66,8 @@ checkEntries <- function(modL, doses, fullMod){
       stop("For model ", nam, ", model entry needs to be equal to NULL")
     if((nam %in% c("emax", "sigEmax", "betaMod", "logistic", "exponential")) & any(pars <= 0))
       stop("For model ", nam, " model entries needs to be positive")
-    if((nam %in% c("emax", "exponential", "quadratic")) & is.matrix(nam))
-      stop("For model ", nam, " parameters need to specified in a vector")
+    if((nam %in% c("emax", "exponential", "quadratic")) & is.matrix(pars))
+      stop("For model ", nam, " parameters need to be specified in a vector")
     if((nam %in% c("sigEmax", "betaMod", "logistic"))){
       if(is.matrix(pars)){
         if(ncol(pars) != 2)
@@ -776,4 +776,4 @@ getModNams <- function(parList){
       mod_nams[i] <- sprintf("linInt (%s)", paste0(parList[[i]], collapse=","))
   }
   mod_nams
-}
+}

R/bFitMod.R

@@ -122,7 +122,7 @@ bFitMod <- function(dose, resp, model, S, placAdj = FALSE,
                     MCMCcontrol = list(), control = NULL, bnds, 
                     addArgs = NULL){
   if(placAdj & model %in% c("linlog", "logistic"))
-    stop("logistic and linlog models can only be fitted with placAdj")
+    stop("logistic and linlog models cannot be fitted to placebo adjusted data")
   nD <- length(dose)
   if (length(resp) != nD) 
     stop("dose and resp need to be of the same size")

R/fitMod_helpers.R

@@ -20,7 +20,7 @@ fit.control <- function(control){
       if(ind){
         stop("gridSize list needs to have names dim1 and dim2")
       } else {
-        if(!is.numeric(control$gridSize$dim1) | !is.numeric(control$gridSize$dim1))
+        if(!is.numeric(control$gridSize$dim1) | !is.numeric(control$gridSize$dim2))
           stop("gridSize$dim1 and gridSize$dim2 need to be numeric")
       }
     }

R/guesst.R

@@ -148,6 +148,8 @@ guesst <- function(d, p, model = c("emax", "exponential", "logistic", "quadratic
              (logistic(Maxd,0,1,par[1],par[2])-e0)-p)^2)
       }
       res <- try(optim(par=res, fn=foolog, d=d, p=p, Maxd=Maxd))
+      if(inherits(res, "try-error"))
+        stop("cannot find guesstimates for specified values")
       if(res$convergence > 0)
         stop("cannot find guesstimates for specified values")
       else res <- res$par
@@ -196,6 +198,8 @@ guesst <- function(d, p, model = c("emax", "exponential", "logistic", "quadratic
              sigEmax(Maxd,0,1,par[1],par[2])-p)^2)
       }
       res <- try(optim(par=res, fn=fooSE, d=d, p=p, Maxd=Maxd))
+      if(inherits(res, "try-error"))
+        stop("cannot find guesstimates for specified values")
       if(res$convergence > 0)
         stop("cannot find guesstimates for specified values")
       else res <- res$par

tests/testthat/test-bFitMod.R

@@ -45,7 +45,7 @@ test_that("bFitMod handles placebo adjustment appropriately", {
   prior <- list(norm = c(0, 10), norm = c(0, 100))
   expect_error(bFitMod(dose = doses, resp = drFit, model = "linlog", S = S, 
                        placAdj = TRUE, type = "Bayes", nSim = 100, prior = prior),
-               "logistic and linlog models can only be fitted with placAdj")
+               "logistic and linlog models cannot be fitted to placebo adjusted data")
 })
 
 test_that("bFitMod correctly handles 'linInt' model", {
@@ -106,4 +106,4 @@ test_that("appropriate methods for bFitMod are defined", {
   expect_true("predict.bFitMod" %in% methods("predict"))
   expect_true("plot.bFitMod" %in% methods("plot"))
   expect_true("coef.bFitMod" %in% methods("coef"))
-})
+})

vignettes/faq.Rmd

@@ -14,10 +14,6 @@ vignette: >
 ---
 
 
-<!-- TODO:
-- [ ] Links to other vignettes and help pages (Ludger)
--->
-
 ```{css, echo=FALSE}
 h2 {
 	font-size: 20px;

vignettes/mult_regimen.Rmd

@@ -100,8 +100,8 @@ plot_estimates <- function(est) {
   ggplot(df, aes(daily_dose, mu_hat)) + geom_point() +
     geom_errorbar(aes(ymin = lb, ymax = ub)) +
     facet_wrap(vars(regimen), labeller = label_both) +
-    xlab("daily dose") + ylab("percent body weight cange") +
-    labs(title = "ANOVA estimates with 95% confindence intervals")
+    xlab("daily dose") + ylab("percent body weight change") +
+    labs(title = "ANOVA estimates with 95% confidence intervals")
 }
 
 est <- example_estimates()
@@ -169,7 +169,6 @@ We also need to calculate the test statistics by hand.
 mct_test <- function(cont_mat, est) {
   cont_cov <- t(cont_mat) %*% est$S_hat %*% cont_mat
   t_stat <- drop(est$mu_hat %*% cont_mat) / sqrt(diag(cont_cov))
-  # FIXME: calling non-exported function
   p <- MCTpval(contMat = cont_mat, corMat = cov2cor(cont_cov),
                df=Inf, tStat=t_stat, alternative = "one.sided")
   ord <- rev(order(t_stat))