Training assessment/Decisions

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Training decision describes decision options for an imaginary assessment designed for training.

Question

What are plausible policies for the Training assessment?

Answer

Training assessment/Decisions: Difference between revisions(-)

Obs	Decision	Option	Variable	Cell	Change	Unit	Amount	Description
1	Exposure policy	Reduce exposure	Training exposure	Year: 2012	Multiply	-	0.5
2	Health promotion	Reduce background risk	Training health impact		Multiply	-	0.9
3	Health promotion	Promotion budget reduced	Training health impact		Multiply	-	1.1

What is the size of population?: + Show code- Hide code # APPLY.DECISIONS ############## apply.decisions takes a decision table and applies that to an assessment. ## dec is a decision data.frame that must have columns Decision, Option, Variable, Cell, Change, Result. It can have several variables. apply.decisions <- function(assessment) { dec <- merge(assessment@decisions, assessment@dependencies, by.x = "Variable", by.y = "Name") colnames(dec)[colnames(dec) == "Result.x"] <- "Result" colnames(dec)[colnames(dec) == "Result.y"] <- "Name" print(xtable(dec), type = 'html') # out <- as.list(unique(dec$Name)) # names(out) <- as.character(unique(dec$Name)) for(variables in unique(dec$Name)) { # Take one variable at a time. dec.var <- dec[dec$Name == variables, ] # dec.var = variable-specific decisions print(xtable(dec.var), type = 'html') scenarios <- data.frame(temp = 1) for(decisions in unique(dec.var$Decision)) { # Add BAU option to each decision and merge decisions. temp <- as.character(dec.var[dec.var$Decision == decisions, "Option"]) temp <- data.frame(Options = c(temp, "BAU")) colnames(temp) <- decisions scenarios <- merge(scenarios, temp) } print(scenarios) var <- assessment@vars[[as.character(dec.var$Name[1])]] var <- merge(scenarios[colnames(scenarios) != "temp"], var) print(var) for(s in 1:nrow(dec.var)) { # Each row in decision handled separately cell <- gsub("^[ \t]+|[ \t]+$", "", as.character(dec$Cell[s])) # Leading and trailing whitespaces removed. cell <- gsub(":[ \t]+", ":", cell) # Whitespaces removed after : cell <- gsub(";[ \t]+", ";", cell) # Whitespaces removed after ; cell <- gsub("[ \t]+:", ":", cell) # Whitespaces removed before : cell <- gsub("[ \t]+;", ";", cell) # Whitespaces removed before ; cell <- strsplit(cell, split = ";") # Separate cell identifiers (indices and locations) cell <- strsplit(cell[[1]], split = ":") cond <- as.character(dec.var$Decision[s]) cond <- var[, cond] == as.character(dec.var$Option[s]) # Only the rows with the relevant option. for(r in 1:length(cell)) { # All Cell conditions extracted and combined with AND. cond <- cond * (var[, cell[[r]][1]] == cell[[r]][2]) } cond <- as.logical(cond) if(dec.var$Change[s] == "Replace" ) {var[cond, "Result"] <- dec.var$Result[s]} if(dec.var$Change[s] == "Add" ) {var[cond, "Result"] <- dec.var$Result[s] + var[cond, "Result"]} if(dec.var$Change[s] == "Multiply") {var[cond, "Result"] <- dec.var$Result[s] * var[cond, "Result"]} } assessment@vars[[variables]] <- var } return(assessment) } cat("Initiation complete. Now starting the model.\n") assessment.training <- make.oassessment("Op_en5677") assessment.training <- apply.decisions(assessment.training)

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