*! version 12 APR2020
help pisareg also see: pisastats pisacmd pisaqreg pisaoaxaca pv repest

Title

pisareg -- Linear regression with PISA data and plausible values

Syntax

pisareg
depvar [indepvars] [if] [in]
[, options]

Main options

cnt(string) Specifies a list of countries for which results will be calculated.
If OECD is specified, then results are provided for all OECD countries participating in this cycle.
Similarly, specifying PARTNERS will produce results for all partner countries and economies participating in this cycle.
Specifying PISA will produce similar results for all countries participating in this cycle.
If ALL is specified, then results are provided for all countries currently in your dataset.
Results can be provided for distinct groups of countries by specifying a list with three letter ISO codes.
For example, option cnt("AUS DEU POL") will produce results for Australia, Germany and Poland.
The OECD average is calculated only when OECD or PISA is specified.
In other cases simple average will be calculated.
If you don't specify this option, the results will be produced for all values of the variable cnt.
This variable must exist in the dataset.

save(filename, ...) save
results to filename. You have to specify this option

Optional

pvindep*(string) where * can be 1, 2 or 3.
Provides a list of plausible values to be included as independent variables in the regression.
You can use the end of any plausible value variable name that starts with pv*.
For example, if you have pv*read variables then use pvindep1(read) to have one plausible value in reading on the rand hand side.
You can specify up to three plausible values as independent variables.
The dependent variable can be also plausible value or any other variable.

over(var) Specifies a categorical variable for which you want to obtain statistics by each category.
The variable must be numerical with a sequence of integers denoting each category.

round(int) Specifies how many decimal places you want to see in results tables. Default is 2.

cycle(int) Specifies which PISA cycle you analyze.
This affects the list of countries recognized as OECD, PISA or PARTNERS in option cnt()
as well as which names of plausible values will be recognized when given as dependent variable.
Default is 2018.

fast Specifying this option dramatically speeds up calculations at the cost of not fully valid estimates of standard errors.
Statistic itself is calculated properly, however, standard errors are calculated using the clustered sandwich estimator (you need to keep schoolid variable in the data).
These standard errors are usually overstimated comparing to the original BRR method.

cons Specify this option if you want to save estimates for the regression constant.

r2() Specify r2(r2_a) to report adjusted R-square or any other scalar returned in e().

Description

You can use pisareg to run linear regression with PISA data. First variable listed after pisareg command is the dependent variable.
You can use any plausible value as the dependent variable but just specify last letters after pv*. Thus, for pv*read just type read.
For any dataset you can type read, math, scie in which case the regression will be run 5 times (or 10 times for 2015 and 2018 data)
on plausible values in reading, mathematics or science, respectively.
For any dataset you can also use proflevel which will run regression 5 times (or 10 times for 2015 and 2018 data) on a dummy indicator
(or any other variable) that is based on any plausible value. This can be used to estimate regression with proficiency levels.
You can also use any plausible value existing in PISA dataset.
For PISA 2000 you can type: math, scie, read, read1, read2, read3, math1, math2, proflevel.
For PISA 2003 you can type: math, scie, read, math1, math2, math3, math4, prob, proflevel.
For PISA 2006 you can type: math, scie, read, intr, supp, eps, isi, use, proflevel.
For PISA 2009 you can type: math, scie, read, era, read1, read2, read3, read4, read5, proflevel.
For PISA 2012 you can type: math, scie, read, macc, macq, macs, macu, mape, mapf, mapi, proflevel.
For PISA 2015 you can type: math, scie, read, scep, sced, scid, skco, skpe, ssph, ssli, sses, proflevel.
For PISA 2018 you can type: math, scie, read, glcm, rcli, rcun, rcer, rtsn, rtml, proflevel.
You can also use pvindep*() option to run regression 5 times (or 10 times for 2015 and 2018 data) with plausible values as independent variables.
The final result will be calculated as a mean of these five regressions (or 10 for 2015 and 2018 data).
You can also specify other variables as dependent variables.
In this case the command will perform a standard linear regression with one dependent variable.
Standard errors are obtained by the BRR method unless fast option is specified.
With fast option clustered sandwich estimator is used.
The command uses survey information provided in the original publicly available PISA datasets.
You need to keep variables like cnt, schoolid, w_fstuwt and w_fst* to be able to use this command.
Pisareg returns matrices with point estimates and standard errors, separately for each over() category.
Type return list after executing pisareg to see what is available.

Examples

. pisareg read escs, cnt(POL) save(example1)

. pisareg read escs gender, cnt(POL) save(example2) cons round(3)

. pisareg joyread escs, over(gender) cnt(AUS POL GBR) save(example3)

. pisareg math escs gender, fast cnt(OECD) cycle(2012) save(example4)

. pisareg read joyread, pvindep1(math) pvindep2(scie) cycle(2009) save(example5) cnt(POL) round(5)

. pisareg joyread escs gender, pvindep1(read) save(example6) cnt(PISA)

References

When using our package please provide this reference in your work:

Maciej Jakubowski & Artur Pokropek (2017), PISATOOLS: Stata module to facilitate analysis of the data from the PISA OECD study, Statistical Software Components, Boston College Department of Economics.

The formulas were taken from:

OECD (2009), PISA Data Analysis Manual: SPSS and SAS, Second Edition, OECD, Paris

OECD (2017), PISA 2015 Technical Report, OECD, Paris

Rubin, D. B. (1987), Multiple imputations for nonresponse in surveys, New York, John Wiley and Sons

Authors

Maciej Jakubowski, Evidence Institute and University of Warsaw, Poland
email: mj@evidenceinstitute.pl

Artur Pokropek, Institute of Philosophy and Sociology, Polish Academy of Sciences

Also see

Other commands in this package pisastats, pisacmd, pisaqreg, pisaoaxaca.

User-written commands pv.ado or repest.ado. Type pv or repest if installed.

Version

Last updated April 2020, by Maciej Jakubowski