ROUT outlier report updated and finalized

dev/BioassayReportROUT.Rmd

@@ -53,10 +53,10 @@ all_l <- REP$all_l
 #ANOVAXLS <- REP$ANOVAXLS
 #XLplot4pl <- REP$XLplot4pl
 DiagnTable <- REP$DiagnTable
-UnRPLAausw <- REP$UnRPLAausw
+
 UnRPLBend <- REP$UnRPLBend
-PLAausw <- REP$PLAausw
-PLbend <- REP$PLBend
+
+BendsROUT <- REP$BendsROUT
 pottab4plXL <- REP$pottab4plXL
 Lim <- REP$Lim
 XLdat2 <- REP$XLdat2
@@ -64,7 +64,8 @@ PureErr <- REP$PureErr
 ro_newROUT <- REP$ro_newROUT
 ROUTplot <- REP$ROUTplot
 ANOVA_ROUT <- REP$ANOVA_ROUT
-
+coeffsMR_ROUT <- REP$RPLAauswROUT
+coeffsMU_ROUT <- REP$UnRPLAauswROUT 
 CIplot <- REP$CIplot
 testsTabROUT <- REP$testsTabROUT
 relpotTestPlot <- REP$relpotTestPlot
@@ -100,7 +101,7 @@ if (!is.null(ro_newROUT)) {
 
 ```{r Over_all, echo=FALSE, comment=NA, warning=NA, message=NA}
 
-browser()
+#browser()
 potFlag <- 0
 if (pottab4plXL["test_result"][[1]][1]=="failed") potFlag <- 1
 AnalysisFlag <- FALSE
@@ -125,7 +126,7 @@ colFmt <- function() {
 
 ## 4pl-regression
 
-Relative potency (absolute and relative confidence limits) are shown in Table 3. `r if(PureErr) {"Pure Error is used for calculations."}` 
+Relative potency (absolute and relative confidence limits) BEFORE EXCLUSION of potential outliers are shown in Table 3 for information. `r if(PureErr) {"Pure Error is used for calculations."}` 
 `r if (!PureErr) {"RMSE of restricted model is used for confidence limit calculation."}`
 
 ```{r Pot_tab4pl, echo=FALSE, comment=NA, warning=NA, message=NA}
@@ -154,6 +155,8 @@ plot(ROUTplot)
 ```
 
 
+# Results after exclusion of potential outliers
+
 ## ANOVA table
 
 The ANOVA of the unconstrained model is listed in table 4. Bates and Watts [4] proposed a test on parallelism which compares the residual sum of squares of the restricted model (ResRSSE) with the residual sum of squares of the unrestricted model (UnresRSSE). If the UnresRSSE is significantly smaller than the ResRSSE, the p-value of "Non-parallelism" is smaller than 0.05 (line 4 in table 4). This test is for information only as it may be overly sensitive in case of small overall variability of the data. 
@@ -200,7 +203,7 @@ cat("  1 ... test failed (for EQ tests: CL not within limits);")
 ```{r AST_Ergebn, echo=FALSE, cache=FALSE, warning=FALSE, message=FALSE, tidy=TRUE}
 
 TestsTabFlag <- FALSE
-if (sum(testsTabROUT$test_results)>0) TestsTabFlag <- TRUE
+if (sum(testsTabROUT[-nrow(testsTabROUT),]$test_results)>0) TestsTabFlag <- TRUE
 colFmt2 <- function() {
   
   outputFormat <- knitr::opts_knit$get("rmarkdown.pandoc.to")
@@ -223,35 +226,39 @@ colFmt2 <- function() {
 
 ## Fitting results with curve points
 
-The results of the non-linear fitting procedure for the restricted model (5 parameters) is listed in table 5:
+The results of the non-linear fitting procedure for the restricted model (5 parameters) is listed in Table 6:
 
 ```{r PLAausw, echo=FALSE, warning=FALSE, results='asis'}
 
-kable(PLAausw, format = "markdown", caption= "Restricted 4PL model", digits=3, row.names = F)
+kable(coeffsMR_ROUT , format = "markdown", caption= "Restricted 4PL model", digits=3, row.names = F)
 
 
 ```
 
 
 
-Sebaugh et al proposed bend points for test and reference samples, that define the points with highest turning behavior. Table 6 lists these bendpoints as well as asymptote points ~ twice as far from the center as the bendpoints.
-
-```{r PLBend, echo=FALSE, warning=FALSE, results='asis'}
-
-kable(PLbend, format = "markdown", caption= "Bendpoints and asymptote points of restricted 4PL model", digits=3)
-
-
-```
-
 The results of the non-linear fitting procedure for the unrestricted model (8 parameters) is listed in table 7:
 
 ```{r UnRPLAausw, echo=FALSE, warning=FALSE, results='asis'}
 
-kable(UnRPLAausw, format = "markdown", caption= "Unrestricted 4PL model", digits=3, row.names = F)
+kable(coeffsMU_ROUT , format = "markdown", caption= "Unrestricted 4PL model", digits=3, row.names = F)
 
 ```
 
 
+## Bend points and asymptote points
+
+Sebaugh et al. proposed bend points for test and reference samples, that define the points with highest turning behavior. Table 6 lists these bendpoints as well as asymptote points ~ twice as far from the center as the bendpoints.
+
+```{r PLBend, echo=FALSE, warning=FALSE, results='asis'}
+
+
+BendsROUT2 <- BendsROUT[1:8,]
+kable(BendsROUT2, format = "markdown", caption= "Bendpoints and asymptote points of restricted 4PL model", digits=3)
+
+
+```
+
 
 # Signature