Reading in the data
## Linear mixed model fit by REML. t-tests use Satterthwaite's method [
## lmerModLmerTest]
## Formula:
## comb08 ~ displ + drive + cylinders + fuelType1 + year + cylinders:displ +
## (1 | make)
## Data: normalcars
##
## REML criterion at convergence: 1339.8
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -2.3019 -0.5118 -0.1064 0.3288 6.2211
##
## Random effects:
## Groups Name Variance Std.Dev.
## make (Intercept) 0.8984 0.9479
## Residual 14.9925 3.8720
## Number of obs: 242, groups: make, 15
##
## Fixed effects:
## Estimate Std. Error df t value Pr(>|t|)
## (Intercept) -340.27485 52.16381 231.17836 -6.523 4.29e-10 ***
## displ -6.15855 1.08896 230.03176 -5.655 4.59e-08 ***
## driveAll-Wheel Drive 0.59863 1.62040 231.99601 0.369 0.712142
## driveFront-Wheel Drive 3.13920 1.25789 231.47612 2.496 0.013272 *
## driveRear-Wheel Drive 0.91405 1.28097 230.91126 0.714 0.476219
## cylinders -1.71129 0.63994 227.69497 -2.674 0.008035 **
## fuelType1Premium Gasoline -8.48482 2.14822 231.36081 -3.950 0.000104 ***
## fuelType1Regular Gasoline -7.45351 2.01955 230.47926 -3.691 0.000279 ***
## year 0.19256 0.02568 231.15899 7.498 1.38e-12 ***
## displ:cylinders 0.52375 0.14311 228.35717 3.660 0.000314 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Correlation of Fixed Effects:
## (Intr) displ drA-WD drF-WD drR-WD cylndr flT1PG flT1RG year
## displ 0.005
## drvAll-WhlD -0.008 0.057
## drvFrnt-WhD -0.242 0.104 0.680
## drvRr-WhlDr -0.395 -0.047 0.581 0.832
## cylinders -0.261 0.240 0.079 0.017 0.054
## flTyp1PrmmG 0.082 -0.063 -0.015 -0.022 -0.044 -0.111
## flTyp1RglrG 0.011 -0.097 -0.009 0.008 0.024 -0.103 0.926
## year -0.998 -0.039 -0.015 0.217 0.378 0.221 -0.113 -0.043
## dspl:cylndr 0.148 -0.850 -0.032 -0.033 0.002 -0.682 0.089 0.113 -0.104## $make
## (Intercept)
## Chevrolet 0.57784454
## Ford -0.19158763
## Honda -0.36348392
## Hyundai 0.45468666
## Kia -0.80859908
## Mazda -0.45919538
## MINI 0.04612310
## Mitsubishi -0.39313936
## Nissan 0.31325589
## Peugeot -0.23710117
## Saturn -0.03970037
## Subaru 0.21683824
## Suzuki -0.21047855
## Toyota 1.64147280
## Volkswagen -0.54693575
##
## with conditional variances for "make"## List of 1
## $ make:'data.frame': 15 obs. of 1 variable:
## ..$ (Intercept): num [1:15] 0.578 -0.192 -0.363 0.455 -0.809 ...
## ..- attr(*, "postVar")= num [1, 1, 1:15] 0.209 0.296 0.505 0.489 0.562 ...
## - attr(*, "class")= chr "ranef.mer"## $make
## $make
