Concise formatting of significances in R (GPL3 license).

Please see Adding polished significance summaries to papers using R for some discussion.

See also:

Used to render the support material for Proofing statistics in papers.


sigr is a small package that concentrates on computing summary statistics and reporting in an appropriate format.

For example here is formatting the quality of a logistic regression.

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)
summary(model)
## 
## Call:
## glm(formula = y ~ x, family = binomial, data = d)
## 
## Deviance Residuals: 
##      Min        1Q    Median        3Q       Max  
## -1.37180  -1.09714  -0.00811   1.08024   1.42939  
## 
## Coefficients:
##             Estimate Std. Error z value Pr(>|z|)
## (Intercept)  -0.7455     1.6672  -0.447    0.655
## x             0.1702     0.3429   0.496    0.620
## 
## (Dispersion parameter for binomial family taken to be 1)
## 
##     Null deviance: 11.090  on 7  degrees of freedom
## Residual deviance: 10.837  on 6  degrees of freedom
## AIC: 14.837
## 
## Number of Fisher Scoring iterations: 4
library("sigr")
cat(render(wrapChiSqTest(model),
           pLargeCutoff=1, format='markdown'))

Chi-Square Test summary: pseudo-R2=0.023 (χ2(1,N=8)=0.25, p=0.61).