sigr formatting
In sigr: Succinct and Correct Statistical Summaries for Reports

Examples of sigr formatting. Inspired by APA format (American Psychological Association), but not fully compliant. Discussed here.

Please see the APA stat guidelines for more notes.

Simple formatting.

library("sigr")
sigr::getRenderingFormat()
cat(render(wrapSignificance(1/300)))

F-test examples (quality of a numeric model of a numeric outcome).

cat(render(wrapFTestImpl(numdf=2,dendf=55,FValue=5.56)))

d <- data.frame(x=0.2*(1:20))
d$y <- cos(d$x)
model <- lm(y~x,data=d)
d$prediction <- predict(model,newdata=d)
print(summary(model))

cat(render(wrapFTest(model),pSmallCutoff=1.0e-12))
cat(render(wrapFTest(d,'prediction','y'),
                              pSmallCutoff=1.0e-12))

Chi-squared test examples (quality of a probability model of a two category outcome).

d <- data.frame(x=c(1,2,3,4,5,6,7,7),
       y=c(TRUE,FALSE,FALSE,FALSE,TRUE,TRUE,TRUE,FALSE))
model <- glm(y~x,data=d,family=binomial)
model$converged
summary(model)
d$pred <- predict(model,type='response',newdata=d)

cat(render(wrapChiSqTest(model),pLargeCutoff=1))
cat(render(wrapChiSqTest(d,'pred','y'),pLargeCutoff=1))

d <- data.frame(x=c(1,2,3,4,5,6,7,7),
               y=c(1,1,2,2,3,3,4,4))
ct <- cor.test(d$x,d$y)

cat(render(wrapCorTest(ct)))

d <- data.frame(x=c('b','a','a','a','b','b','b'),
                y=c('1','1','1','2','2','2','2'))
ft <- fisher.test(table(d))

cat(render(wrapFisherTest(ft),pLargeCutoff=1))

d <- data.frame(x=c(1,2,3,4,5,6,7,7),
                y=c(1,1,2,2,3,3,4,4))
ft <- t.test(d$x,d$y)

cat(render(wrapTTest(ft),pLargeCutoff=1))

parallelCluster <- NULL
#parallelCluster <- parallel::makeCluster(parallel::detectCores())

set.seed(25325)
d <- data.frame(x1=c(1,2,3,4,5,6,7,7),
                y=c(FALSE,TRUE,FALSE,FALSE,
                    TRUE,TRUE,FALSE,TRUE))
d <- rbind(d,d,d,d)
sigr::resampleTestAUC(d,'x1','y',TRUE,
                nrep=200,
                parallelCluster=parallelCluster)

set.seed(25325)
d <- data.frame(x1=c(1,2,3,4,5,6,7,7),
                x2=1,
                y=c(FALSE,TRUE,FALSE,FALSE,
                    TRUE,TRUE,FALSE,TRUE))
d <- rbind(d,d,d,d)
sigr::testAUCpair(d,'x1','x2','y',TRUE,
                    nrep=200,
                    parallelCluster=parallelCluster)
if(!is.null(parallelCluster)) {
  parallel::stopCluster(parallelCluster)
}

permutationScoreModel

set.seed(25325)
y <- 1:5
m <- c(1,1,2,2,2)
cor.test(m,y,alternative='greater')
f <- function(modelValues, yValues) { cor(modelValues, yValues) }
sigr::permutationScoreModel(m,y,f)

resampleScoreModel

set.seed(25325)
y <- 1:5
m1 <- c(1,1,2,2,2)
cor.test(m1,y,alternative='greater')
f <- function(modelValues,yValues) {
  if((sd(modelValues)<=0)||(sd(yValues)<=0)) {
    return(0)
  }
  cor(modelValues,yValues)
}
s <- sigr::resampleScoreModel(m1,y,f)
print(s)
z <- s$observedScore/s$sd  # always check size of z relative to bias!
pValue <- pt(z,df=length(y)-2,lower.tail=FALSE)
pValue

resampleScoreModelPair

set.seed(25325)
y <- 1:5
m1 <- c(1,1,2,2,2)
m2 <- c(1,1,1,1,2)
cor(m1,y)
cor(m2,y)
f <- function(modelValues,yValues) {
  if((sd(modelValues)<=0)||(sd(yValues)<=0)) {
    return(0)
  }
  cor(modelValues,yValues)
}
sigr::render(sigr::resampleScoreModelPair(m1,m2,y,f),
             pLargeCutoff=1,format='ascii')