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ILSA's league tables

leaguetable.Rd

Estimates the mean score for all countries within a cycle of an ILSA. Arguments method, reps, and var, are extracted from autoILSA and can be overridden by the user.

Usage

leaguetable(
  df,
  study = NULL,
  year,
  subject = NULL,
  specification = NULL,
  addCI = TRUE,
  alpha = 0.05,
  method = NULL,
  reps = NULL,
  fixN = TRUE
)

Arguments

df

a data frame.

study

an optional character vector indicating the ILSA name, for a list of available ILSA, check autoILSA. If NULL, the ILSA name will be determined by the column names in the data frame.

year

a numeric vector indicating the ILSA name, for a list of available cycles, check autoILSA.

subject

an optional character vector indicating the subject for a list of available ILSA, check autoILSA.

specification

a character value indicating extra specification like grade (e.g., "G8" for TIMSS) or subject (e.g., "Math" for TIMSSADVANCED).

addCI

a logical value indicating if confidence intervals should be added. Defaults is TRUE.

alpha

a numeric value indicating confidence level.

method

a string indicating the name of the replication method. Available options are: "JK2-full", "JK2-half", "FAY-0.5", and "JK2-half-1PV".

Additionally, ILSA names can be used, defaulting into:

  • "TIMSS", "PIRLS", or "LANA" for "JK2-full";

  • "ICILS", "ICCS", or "CIVED" for "JK2-half";

  • "PISA" or "TALIS" for "FAY-0.5";

  • and "oldTIMSS", "oldPIRLS", or "RLII" for "JK2-half-1PV".

Note that "oldTIMSS" and "oldPIRLS" refer to the method used for TIMSS and PIRLS before 2015, where within imputation variance is estimated using only 1 plausible value.

reps

an integer indicating the number of replications to be created. If NULL the maximum number of zones will be used.

fixN

a logical value indicating if data should be "fixed" to meet official criteria. For example, reducing the sample for certain countries in TIMSS 1995. Default is TRUE.

Value

a data frame.

Examples

data(timss99)
leaguetable(df = timss99, year = 1999)
#>   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 583.3467