Description Usage Format Source References Examples

Data on maths performance, gender, some problem-solving variables and some school resource variables. This is actually a weighted survey: see `withPV.survey.design`

in the `survey`

package for a better analyis.

1 | ```
data("pisamaths")
``` |

A data frame with 4291 observations on the following 26 variables.

`SCHOOLID`

School ID

`CNT`

Country id: a factor with levels

`New Zealand`

`STRATUM`

a factor with levels

`NZL0101`

`NZL0102`

`NZL0202`

`NZL0203`

`OECD`

Is the country in the OECD?

`STIDSTD`

Student ID

`ST04Q01`

Gender: a factor with levels

`Female`

`Male`

`ST14Q02`

Mother has university qualifications

`No`

`Yes`

`ST18Q02`

Father has university qualifications

`No`

`Yes`

`MATHEFF`

Mathematics Self-Efficacy: numeric vector

`OPENPS`

Mathematics Self-Efficacy: numeric vector

`PV1MATH`

,`PV2MATH`

,`PV3MATH`

,`PV4MATH`

,`PV5MATH`

'Plausible values' (multiple imputations) for maths performance

`W_FSTUWT`

Design weight for student

`SC35Q02`

Proportion of maths teachers with professional development in maths in past year

`PCGIRLS`

Proportion of girls at the school

`PROPMA5A`

Proportion of maths teachers with ISCED 5A (math major)

`ABGMATH`

Does the school group maths students: a factor with levels

`No ability grouping between any classes`

`One of these forms of ability grouping between classes for s`

`One of these forms of ability grouping for all classes`

`SMRATIO`

Number of students per maths teacher

`W_FSCHWT`

Design weight for school

`condwt`

Design weight for student given school

A subset extracted from the `PISA2012lite`

R package, https://github.com/pbiecek/PISA2012lite

OECD (2013) PISA 2012 Assessment and Analytical Framework: Mathematics, Reading, Science, Problem Solving and Financial Literacy. OECD Publishing.

1 2 3 4 5 6 7 8 9 | ```
data(pisamaths)
means<-withPV(list(maths~PV1MATH+PV2MATH+PV3MATH+PV4MATH+PV5MATH), data=pisamaths,
action= quote(by(maths, ST04Q01, mean)), rewrite=TRUE)
means
models<-withPV(list(maths~PV1MATH+PV2MATH+PV3MATH+PV4MATH+PV5MATH), data=pisamaths,
action= quote(lm(maths~ST04Q01*PCGIRLS)), rewrite=TRUE)
summary(MIcombine(models))
``` |

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