# Probability of false positives

This utility calculates the expected probability of numbers of false positive results to a test for a given sample size and test specificity, assuming the sample is from an uninfected population. It answers the question: '*For a given sample size and test specificity, and assuming that all animals are uninfected, what is the probability that there will be 1, 2, 3 etc false positives*?'. It also answers the related questions: '

*What is the probability of x (1, 2, 3, etc)*? and

**or more**false positive results*What is the probability of x (1, 2, 3, etc)*?'

**or less**false positive resultsInputs are the sample size tested and the test specificity.

Outputs are a table and graph of probabilities associated with each of the likely number of false positive results.

No results

No example available

No references available

###################################### # Program to calculate numbers of false positives ###################################### rm(list = ls()) # check version and load header script test<- ifelse(length(commandArgs()) < 3, TRUE, FALSE) fpath<- ifelse(test, "webRootUrl", "rtoolsPath") # load header scripts source(paste(fpath, "R/epi_head.R", sep = "")) source(paste(fpath, "R/HTMLStream.R", sep = "")) source(paste(fpath, "R/epitools_functions.r", sep = "")) # extract command arguments a1<- type.convert(a0[8:9]) # cat(a0) # cat(a1) digits<- 4 p<- a1[1] n<- a1[2] names(a1)<- c("Probability of true result (specificity)", "Sample size") filename <- digest(Sys.time()) tmp.path<- paste(fpath, "tmp/", sep = "") tmp.file<- paste(fpath, "tmp/", filename, sep = "") sinkfile<- paste(fpath, "tmp/", filename, ".txt", sep="") # fpath, graphfile<- paste(fpath, "tmp/", filename, ".png", sep="") # table of inputs inputs<- array("", dim = c(length(a1), 1)) inputs[1:2, 1]<- a1 rownames(inputs)<- names(a1) results<- array(0, dim = c(n+1, 4)) colnames(results)<- c("Number of false positives (x)", "P(pos=x)", "P(pos<= x)", "P(pos>=x)") results1<- results results[,1]<- 0:n results[,2]<- dbinom(0:n, n, (1-p)) results[1,3]<- results[1,2] results[1,4]<- 1 for(i in 1:n+1) { results[i,3]<- results[i-1,3] + results[i,2] results[i,4]<- results[i-1,4] - results[i-1,2] } results<- round(results, digits) results1[,2:4]<- format(results[,2:4], scientific = F) results1[,1]<- results[,1] max<- match(0, results[,4])+1 # graph results Title<-"Probability of varying numbers of false +ve" OpenGraphOutput(graphfile, pointsize = 12, ht = 6, wd = 8) cols<- c("darkblue", "darkgreen", "red", "magenta", "brown", "purple") plot(x = results[1:max,1], y = results[1:max,2], ylim = c(0,1), xlab = colnames(results)[1], ylab= "Probability", main=Title, col = cols[1], type = "o", pch=3) lines(x = results[1:max,1], y = results[1:max,3], col = cols[2], type = "o", pch=8) lines(x = results[1:max,1], y = results[1:max,4], col = cols[3], type = "o", pch=4) legend("right", colnames(results)[2:4], col = cols[1:3], pch = c(3, 8, 4), cex = 0.8) sink(sinkfile) CloseGraphOutput("R") sink() # write to html and file heading<- "Probability of false positives" subheadings<- "" tmp.file<- paste(fpath, "tmp/", filename, sep = "") output<- html.output(heading, subheadings = "", inputs, results = list(results1[1:max,]), graphs = graphfile, graph.headings = "Distribution of false positives", show.inputs = T, show.graphs = T, tmp.file, result.txt = "") write.html(output, tmp.file) cat(output)