Fitting linear model / ANOVA by group [duplicate]

守給你的承諾、 提交于 2019-11-28 14:10:58
李哲源

I think you are looking for by facility in R.

fit <- with(mhw, by(mhw, Quad, function (dat) lm(grain ~ straw, data = dat)))

Since you have 4 levels in Quad, you end up with 4 linear models in fit, i.e., fit is a "by" class object (a type of "list") of length 4.

To get coefficient for each model, you can use

sapply(fit, coef)

To produce model summary, use

lapply(fit, summary)

To export ANOVA table, use

lapply(fit, anova)

As a reproducible example, I am taking the example from ?by:

tmp <- with(warpbreaks,
            by(warpbreaks, tension,
               function(x) lm(breaks ~ wool, data = x)))

class(tmp)
# [1] "by"

mode(tmp)
# [1] "list"

sapply(tmp, coef)

#                    L         M         H
#(Intercept)  44.55556 24.000000 24.555556
#woolB       -16.33333  4.777778 -5.777778

lapply(tmp, anova)

#$L
#Analysis of Variance Table
#
#Response: breaks
#          Df Sum Sq Mean Sq F value  Pr(>F)  
#wool       1 1200.5 1200.50  5.6531 0.03023 *
#Residuals 16 3397.8  212.36                  
#---
#Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
#
#$M
#Analysis of Variance Table
#
#Response: breaks
#          Df  Sum Sq Mean Sq F value Pr(>F)
#wool       1  102.72 102.722  1.2531 0.2795
#Residuals 16 1311.56  81.972               
#
#$H
#Analysis of Variance Table
#
#Response: breaks
#          Df  Sum Sq Mean Sq F value Pr(>F)
#wool       1  150.22 150.222  2.3205 0.1472
#Residuals 16 1035.78  64.736

I was aware of this option, but not familiar with it. Thanks to @Roland for providing code for the above reproducible example:

library(nlme)
lapply(lmList(breaks ~ wool | tension, data = warpbreaks), anova)

For your data I think it would be

fit <- lmList(grain ~ straw | Quad, data = mhw)
lapply(fit, anova)

You don't need to install nlme; it comes with R as one of recommended packages.

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