R2MLwiN (version 0.8-2)

reading1: Students' reading attainment in inner London infant schools.

Description

Reading score data for 407 pupils across 6 occasions.

Format

A data frame with 407 observations on the following 13 variables:

id

Unique pupil identifying code.

age1

Age at occasion 1.

read1

Reading score at occasion 1.

age2

Age at occasion 2.

read2

Reading score at occasion 2.

age3

Age at occasion 3.

read3

Reading score at occasion 3.

age4

Age at occasion 4.

read4

Reading score at occasion 4.

age5

Age at occasion 5.

read5

Reading score at occasion 5.

age6

Age at occasion 6.

read6

Reading score at occasion 6.

Source

Rasbash, J., Charlton, C., Browne, W.J., Healy, M. and Cameron, B. (2009) MLwiN Version 2.1. Centre for Multilevel Modelling, University of Bristol. Rasbash, J., Steele, F., Browne, W.J., Goldstein, H. (2012) A User's Guide to MLwiN v2.26. University of Bristol: Centre for Multilevel Modelling. Tizard, B., Blatchford, P., Burke, J. & Farquhar, C. (1988). Young children at school in the inner city. Hove, Sussex: Lawrence Erlbaum.

Details

The reading1 dataset is one of the sample datasets provided with the multilevel-modelling software package MLwiN (Rasbash et al., 2009), and was analysed in Tizard et al. (1988); see also Rasbash et al. (2012) for further details.

Examples

## Not run: 
# # from demo(UserGuide13)
# 
# data(reading1, package = "R2MLwiN")
# summary(reading1)
# 
# reading1[reading1 == -10] <- NA
# 
# summary(reading1)
# 
# reading <- reshape(reading1, idvar = "student", timevar = "id",
#                    varying = c("read1", "age1", "read2", "age2", "read3", "age3",
#                    "read4", "age4", "read5", "age5", "read6", "age6"),
#                    sep = "", direction = "long")
# 
# reading <- reading[c("student", "id", "age", "read")]
# reading <- reading[order(reading$student, reading$id), ]
# 
# colnames(reading) <- c("student", "occasion", "age", "reading")
# rownames(reading) <- NULL
# 
# summary(reading)
# 
# head(reading, 5)
# 
# tab <- aggregate(reading ~ occasion, reading,
#                  function(x) c(N = length(x), mean = mean(x), sd = sd(x)))
# tab <- rbind(tab, c(NA, NA))
# tab$reading[7, ] <- c(length(na.omit(reading$reading)),
#                       mean(na.omit(reading$reading)),
#                       sd(na.omit(reading$reading)))
# rownames(tab)[7] <- "Total"
# tab
# 
# tab <- aggregate(age ~ occasion, reading,
#                  function(x) c(N = length(x), mean = mean(x), sd = sd(x)))
# tab <- rbind(tab, c(NA, NA))
# tab$age[7, ] <- c(length(na.omit(reading$age)),
#                   mean(na.omit(reading$age)),
#                   sd(na.omit(reading$age)))
# rownames(tab)[7] <- "Total"
# tab
# 
# (mymodel1 <- runMLwiN(reading ~ 1 + (1 | student) + (1 | occasion),
#                       data = reading))
# ## End(Not run)