Description Usage Format Source References Examples

Exam scores of 4,059 students from 65 schools in Inner London.

1 |

A data frame with 4059 observations on the following 9 variables.

- school
School ID - a factor.

- normexam
Normalized exam score.

- schgend
School gender - a factor. Levels are

`mixed`

,`boys`

, and`girls`

.- schavg
School average of intake score.

- vr
Student level Verbal Reasoning (VR) score band at intake - a factor. Levels are

`bottom 25%`

,`mid 50%`

, and`top 25%`

.- intake
Band of student's intake score - a factor. Levels are

`bottom 25%`

,`mid 50%`

and`top 25%`

./- standLRT
Standardised LR test score.

- sex
Sex of the student - levels are

`F`

and`M`

.- type
School type - levels are

`Mxd`

and`Sngl`

.- student
Student id (within school) - a factor

http://multilevel.ioe.ac.uk/softrev/exam.html

Goldstein, H., Rasbash, J., et al (1993). A multilevel analysis of
school examination results. *Oxford Review of Education* 19: 425-433

1 2 3 4 5 |

```
Loading required package: lme4
Loading required package: Matrix
'data.frame': 4059 obs. of 10 variables:
$ school : Factor w/ 65 levels "1","2","3","4",..: 1 1 1 1 1 1 1 1 1 1 ...
$ normexam: num 0.261 0.134 -1.724 0.968 0.544 ...
$ schgend : Factor w/ 3 levels "mixed","boys",..: 1 1 1 1 1 1 1 1 1 1 ...
$ schavg : num 0.166 0.166 0.166 0.166 0.166 ...
$ vr : Factor w/ 3 levels "bottom 25%","mid 50%",..: 2 2 2 2 2 2 2 2 2 2 ...
$ intake : Factor w/ 3 levels "bottom 25%","mid 50%",..: 1 2 3 2 2 1 3 2 2 3 ...
$ standLRT: num 0.619 0.206 -1.365 0.206 0.371 ...
$ sex : Factor w/ 2 levels "F","M": 1 1 2 1 1 2 2 2 1 2 ...
$ type : Factor w/ 2 levels "Mxd","Sngl": 1 1 1 1 1 1 1 1 1 1 ...
$ student : Factor w/ 650 levels "1","2","3","4",..: 143 145 142 141 138 155 158 115 117 113 ...
school normexam schgend schavg
14 : 198 Min. :-3.666072 mixed:2169 Min. :-0.75596
17 : 126 1st Qu.:-0.699505 boys : 513 1st Qu.:-0.14934
18 : 120 Median : 0.004322 girls:1377 Median :-0.02020
49 : 113 Mean :-0.000114 Mean : 0.00181
8 : 102 3rd Qu.: 0.678759 3rd Qu.: 0.21053
15 : 91 Max. : 3.666091 Max. : 0.63766
(Other):3309
vr intake standLRT sex type
bottom 25%: 640 bottom 25%:1176 Min. :-2.93495 F:2436 Mxd :2169
mid 50% :2263 mid 50% :2344 1st Qu.:-0.62071 M:1623 Sngl:1890
top 25% :1156 top 25% : 539 Median : 0.04050
Mean : 0.00181
3rd Qu.: 0.61906
Max. : 3.01595
student
20 : 34
54 : 34
15 : 33
22 : 33
31 : 33
59 : 33
(Other):3859
Linear mixed model fit by REML ['lmerMod']
Formula: normexam ~ standLRT + sex + schgend + (1 | school)
Data: Exam
REML criterion at convergence: 9347.674
Random effects:
Groups Name Std.Dev.
school (Intercept) 0.293
Residual 0.750
Number of obs: 4059, groups: school, 65
Fixed Effects:
(Intercept) standLRT sexM schgendboys schgendgirls
-0.001049 0.559754 -0.167392 0.177691 0.158997
Linear mixed model fit by REML ['lmerMod']
Formula: normexam ~ standLRT * sex + schgend + (1 | school)
Data: Exam
REML criterion at convergence: 9353.204
Random effects:
Groups Name Std.Dev.
school (Intercept) 0.2930
Residual 0.7501
Number of obs: 4059, groups: school, 65
Fixed Effects:
(Intercept) standLRT sexM schgendboys schgendgirls
-0.0008435 0.5574520 -0.1673333 0.1776492 0.1587870
standLRT:sexM
0.0051121
Linear mixed model fit by REML ['lmerMod']
Formula: normexam ~ standLRT * sex + schgend + (1 | school)
Data: Exam
REML criterion at convergence: 9353.204
Random effects:
Groups Name Std.Dev.
school (Intercept) 0.2930
Residual 0.7501
Number of obs: 4059, groups: school, 65
Fixed Effects:
(Intercept) standLRT sexM schgendboys schgendgirls
-0.0008435 0.5574520 -0.1673333 0.1776492 0.1587870
standLRT:sexM
0.0051121
```

mlmRev documentation built on May 29, 2017, 8 p.m.

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