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Table 7.1 on page 126 using the pupcross dataset.
Part 1: Intercept only.
library(foreign)
library(lme4)
pupcross<-read.dta("http://www.ats.ucla.edu/stat/stata/examples/mlm_ma_hox/pupcross.dta")
m1<-lmer(achiev ~ (1|sschool) + (1|pschool), pupcross, REML=FALSE)
summary(m1)
Linear mixed model fit by maximum likelihood
Formula: achiev ~ (1 | sschool) + (1 | pschool)
Data: pupcross
AIC BIC logLik deviance REMLdev
2326 2345 -1159 2318 2321
Random effects:
Groups Name Variance Std.Dev.
pschool (Intercept) 0.169348 0.41152
sschool (Intercept) 0.065401 0.25574
Residual 0.513169 0.71636
Number of obs: 1000, groups: pschool, 50; sschool, 30
Fixed effects:
Estimate Std. Error t value
(Intercept) 6.34865 0.07831 81.07
Part 2: intercept plus pupil level variables
m2<-lmer(achiev ~ pupsex + pupses +(1|sschool) + (1|pschool), pupcross, REML=FALSE)
summary(m2)
Linear mixed model fit by maximum likelihood
Formula: achiev ~ pupsex + pupses + (1 | sschool) + (1 | pschool)
Data: pupcross
AIC BIC logLik deviance REMLdev
2255 2285 -1122 2243 2258
Random effects:
Groups Name Variance Std.Dev.
pschool (Intercept) 0.169009 0.41111
sschool (Intercept) 0.063606 0.25220
Residual 0.474255 0.68866
Number of obs: 1000, groups: pschool, 50; sschool, 30
Fixed effects:
Estimate Std. Error t value
(Intercept) 5.75548 0.10527 54.67
pupsexgirl 0.26131 0.04564 5.73
pupses 0.11409 0.01610 7.09
Correlation of Fixed Effects:
(Intr) ppsxgr
pupsexgirl -0.254
pupses -0.643 0.075
Part 3: primary by secondary School crossed with pupil and school variables
m3<-lmer(achiev ~ pupsex + pupses + pdenom + sdenom +(1|sschool) + (1|pschool), pupcross, REML=FALSE)
summary(m3)
Linear mixed model fit by maximum likelihood
Formula: achiev ~ pupsex + pupses + pdenom + sdenom + (1 | sschool) + (1 | pschool)
Data: pupcross
AIC BIC logLik deviance REMLdev
2253 2293 -1119 2237 2257
Random effects:
Groups Name Variance Std.Dev.
pschool (Intercept) 0.159410 0.39926
sschool (Intercept) 0.055424 0.23542
Residual 0.474105 0.68855
Number of obs: 1000, groups: pschool, 50; sschool, 30
Fixed effects:
Estimate Std. Error t value
(Intercept) 5.51850 0.14077 39.20
pupsexgirl 0.26308 0.04561 5.77
pupses 0.11356 0.01609 7.06
pdenomyes 0.20412 0.12410 1.64
sdenomyes 0.17615 0.09465 1.86
Correlation of Fixed Effects:
(Intr) ppsxgr pupses pdnmys
pupsexgirl -0.203
pupses -0.472 0.075
pdenomyes -0.524 0.021 0.004
sdenomyes -0.428 0.003 -0.025 -0.014
Part 4: primary by secondary School crossed with pupil and school variables with variable pupses being modeled as a random effect.
m4<-lmer(achiev ~ pupsex + pupses + pdenom + sdenom +(1|sschool)
+ (1|pschool) + (pupses|pschool), pupcross, REML=FALSE)
summary(m4)
Linear mixed model fit by maximum likelihood
Formula: achiev ~ pupsex + pupses + pdenom + sdenom + (1 | sschool) + (1 | pschool) + (pupses | pschool)
Data: pupcross
AIC BIC logLik deviance REMLdev
2246 2300 -1112 2224 2244
Random effects:
Groups Name Variance Std.Dev. Corr
pschool (Intercept) 0.0950452 0.308294
pupses 0.0080183 0.089545 -0.565
pschool (Intercept) 0.0535395 0.231386
sschool (Intercept) 0.0537343 0.231807
Residual 0.4583575 0.677021
Number of obs: 1000, groups: pschool, 50; sschool, 30
Fixed effects:
Estimate Std. Error t value
(Intercept) 5.53241 0.13746 40.25
pupsexgirl 0.25316 0.04530 5.59
pupses 0.11423 0.02047 5.58
pdenomyes 0.19990 0.11764 1.70
sdenomyes 0.16456 0.09343 1.76
Correlation of Fixed Effects:
(Intr) ppsxgr pupses pdnmys
pupsexgirl -0.209
pupses -0.491 0.056
pdenomyes -0.512 0.029 0.006
sdenomyes -0.432 0.006 -0.020 -0.017
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