I have 10 linear models where I only need some information, namely: r-squared, p-value, coefficients of slope and intercept. I managed to extract these values (via ridiculously
Here is a base R solution:
data <- read.csv("./data/so53933238.csv",header=TRUE)
# split by value of CatChro into a list of datasets
dataList <- split(data,data$CatChro)
# process the list with lm(), extract results to a data frame, write to a list
lmResults <- lapply(dataList,function(x){
y <- summary(lm(Qend ~ Rainfall,data = x))
Intercept <- y$coefficients[1,1]
Slope <- y$coefficients[2,1]
rSquared <- y$r.squared
adjRSquared <- y$adj.r.squared
f <- y$fstatistic[1]
pValue <- pf(y$fstatistic[1],y$fstatistic[2],y$fstatistic[3],lower.tail = FALSE)
data.frame(Slope,Intercept,rSquared,adjRSquared,pValue)
})
lmResultTable <- do.call(rbind,lmResults)
# add CatChro indicators
lmResultTable$catChro <- names(dataList)
lmResultTable
...and the output:
> lmResultTable
Slope Intercept rSquared adjRSquared pValue catChro
A3D1 0.0004085644 0.011876543 0.28069553 0.254054622 0.0031181110 A3D1
A3D2 0.0005431693 0.023601325 0.03384173 0.005425311 0.2828170556 A3D2
A3D3 0.0001451185 0.022106960 0.04285322 0.002972105 0.3102578215 A3D3
A3D4 0.0006614213 0.009301843 0.37219027 0.349768492 0.0003442445 A3D4
A3D5 0.0001084626 0.014341399 0.04411669 -0.008987936 0.3741011769 A3D5
A3G1 0.0001147645 0.024432020 0.03627553 0.011564648 0.2329519751 A3G1
A3G2 0.0004583538 0.026079409 0.06449971 0.041112205 0.1045970987 A3G2
A3G3 0.0006964512 0.043537869 0.07587433 0.054383038 0.0670399684 A3G3
A3G4 0.0006442175 0.023706652 0.17337420 0.155404076 0.0032431299 A3G4
A3G5 0.0006658466 0.025994831 0.17227383 0.150491566 0.0077413595 A3G5
>
To render the output in a tabular format in HTML, one can use knitr::kable()
.
library(knitr)
kable(lmResultTable[1:5],row.names=TRUE,digits=5)
...which produces the following output after rendering the Markdown: