To calculate league tables of an ILSA we need to obtain the country
mean of all participant country of a cycle. Of course, we can do this
using repmean(), nevertheless, for certain ILSA all the
relevant information is already incorporated into
ILSAstats. We can check all the available cycles with
autoILSA():
## Options for leaguetable(...):
##
## year:
## CIVED = 1999.
## ICCS = 2009, 2016, 2022.
## ICILS = 2013, 2018, 2023.
## LANA = 2023.
## PIRLS = 2001, 2006, 2011, 2016, 2021.
## RLII = 1991, 2001.
## TIMSS = 1995, 1999, 2003, 2007, 2011, 2015, 2019, 2023.
## TIMSSADVANCED = 1995, 2008, 2015.
## TIMSSLONG = 2023.
##
## specification:
## CIVED = G12, G8.
## ICCS = NULL, G8, G9.
## ICILS = NULL.
## LANA = NULL.
## PIRLS = NULL.
## RLII = NULL.
## TIMSS = G4, G8.
## TIMSSADVANCED = math, physics.
## TIMSSLONG = G45, G89.
##
## subject:
## CIVED = civic knowledge.
## ICCS = civic knowledge.
## ICILS = cil, ct.
## LANA = math, reading.
## PIRLS = reading.
## RLII = reading.
## TIMSS = math, science.
## TIMSSADVANCED = math, physics.
## TIMSSLONG = math23, math24, mathchange, science23, science24, sciencechange.There is a total of 68 combinations.
For producing an automatic league table we can use
leaguetable(), which contains the following arguments:
df: the data frame with the ILSA data.study: the name of the study as it appears in
ILSAinfo$pvs$study.year: the year of the cycle.subject: the name of the subject as it appears in
ILSAinfo$pvs$year. If left NULL all subjects
will be estimated.specification: a string indicating extra specification
for the identifying the study if it is necessary, as it appears in
ILSAinfo$pvs$study2. If left NULL it is
equivalent to "-".method: the method to use. If left NULL
the default method will be used.fixN: a logical value indicating if cases should be
removed to match official results. This is necessary in some studies
like TIMSS 1995, in which the public data includes cases that are not
used for producing the league tables.We can use timss99 data to calculate the official league
table published in the TIMSS 1999 report using:
## study study2 year subject group N mean se CIdown CIup
## 1 TIMSS G8 1999 math Chile 1076 392.7611 5.45224 382.0749 403.4473
## 2 TIMSS G8 1999 math Japan 885 578.4152 2.95280 572.6278 584.2026
## 3 TIMSS G8 1999 math Taiwan 1039 590.4357 4.94637 580.7410 600.1304## study study2 year subject group N mean se CIdown CIup
## 1 TIMSS G8 1999 science Chile 1076 420.5514 4.78608 411.1708 429.9319
## 2 TIMSS G8 1999 science Japan 885 550.6614 2.59819 545.5690 555.7538
## 3 TIMSS G8 1999 science Taiwan 1039 573.3537 5.09858 563.3606 583.3467## study study2 year subject group N mean se CIdown CIup
## 1 TIMSS G8 1999 math Chile 1076 392.7611 5.45224 382.0749 403.4473
## 2 TIMSS G8 1999 math Japan 885 578.4152 2.95280 572.6278 584.2026
## 3 TIMSS G8 1999 math Taiwan 1039 590.4357 4.94637 580.7410 600.1304
## 4 TIMSS G8 1999 science Chile 1076 420.5514 4.78608 411.1708 429.9319
## 5 TIMSS G8 1999 science Japan 885 550.6614 2.59819 545.5690 555.7538
## 6 TIMSS G8 1999 science Taiwan 1039 573.3537 5.09858 563.3606 583.3467Nevertheless, we can also change the method. For example, we can do
this to compare TIMSS 1999 to TIMSS 2023, therefore, we would need to
use the method "TIMSS" instead of
"oldTIMSS":
## study study2 year subject group N mean se CIdown CIup
## 1 TIMSS G8 1999 math Chile 1076 392.7611 5.46288 382.0540 403.4681
## 2 TIMSS G8 1999 math Japan 885 578.4152 2.80539 572.9167 583.9137
## 3 TIMSS G8 1999 math Taiwan 1039 590.4357 5.00692 580.6223 600.2491
## 4 TIMSS G8 1999 science Chile 1076 420.5514 4.86369 411.0187 430.0840
## 5 TIMSS G8 1999 science Japan 885 550.6614 2.53919 545.6847 555.6381
## 6 TIMSS G8 1999 science Taiwan 1039 573.3537 5.01030 563.5337 583.1737We can calculate the difference between groups using
repmeandif():
## study study2 year subject group1 group2 dif se tvalue df
## 1 TIMSS G8 1999 math Chile Chile 0.00000 7.71064 0.00000 2150
## 2 TIMSS G8 1999 math Chile Japan -185.65410 6.20049 -29.94184 1959
## 3 TIMSS G8 1999 math Chile Taiwan -197.67460 7.36163 -26.85202 2113
## 4 TIMSS G8 1999 math Japan Chile 185.65410 6.20049 29.94184 1959
## 5 TIMSS G8 1999 math Japan Japan 0.00000 4.17589 0.00000 1768
## 6 TIMSS G8 1999 math Japan Taiwan -12.02049 5.76069 -2.08664 1922
## 7 TIMSS G8 1999 math Taiwan Chile 197.67460 7.36163 26.85202 2113
## 8 TIMSS G8 1999 math Taiwan Japan 12.02049 5.76069 2.08664 1922
## 9 TIMSS G8 1999 math Taiwan Taiwan 0.00000 6.99522 0.00000 2076
## 10 TIMSS G8 1999 science Chile Chile 0.00000 6.76855 0.00000 2150
## 11 TIMSS G8 1999 science Chile Japan -130.11005 5.44584 -23.89164 1959
## 12 TIMSS G8 1999 science Chile Taiwan -152.80231 6.99301 -21.85072 2113
## 13 TIMSS G8 1999 science Japan Chile 130.11005 5.44584 23.89164 1959
## 14 TIMSS G8 1999 science Japan Japan 0.00000 3.67440 0.00000 1768
## 15 TIMSS G8 1999 science Japan Taiwan -22.69226 5.72242 -3.96550 1922
## 16 TIMSS G8 1999 science Taiwan Chile 152.80231 6.99301 21.85072 2113
## 17 TIMSS G8 1999 science Taiwan Japan 22.69226 5.72242 3.96550 1922
## 18 TIMSS G8 1999 science Taiwan Taiwan 0.00000 7.21048 0.00000 2076
## pvalue
## 1 1.00000
## 2 0.00000
## 3 0.00000
## 4 0.00000
## 5 1.00000
## 6 0.03705
## 7 0.00000
## 8 0.03705
## 9 1.00000
## 10 1.00000
## 11 0.00000
## 12 0.00000
## 13 0.00000
## 14 1.00000
## 15 0.00008
## 16 0.00000
## 17 0.00008
## 18 1.00000