Exam: Exam scores from inner London

In mlmRev: Examples from Multilevel Modelling Software Review

Description

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

Usage

data(Exam)

Format

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

Source

http://www.bristol.ac.uk/cmm/learning/mmsoftware/data-rev.html

References

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

Examples

str(Exam)
summary(Exam)
(fm1 <- lmer(normexam ~ standLRT + sex + schgend + (1|school), Exam))
(fm2 <- lmer(normexam ~ standLRT*sex + schgend + (1|school), Exam))
(fm3 <- lmer(normexam ~ standLRT*sex + schgend + (1|school), Exam))

Example output

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 April 5, 2020, 9:07 a.m.