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Setup for Analysis with Replicate Weights

repsetup.Rd

Creates a list with common arguments used for analysis with replicate weights.

Usage

repsetup(
  repwt = NULL,
  repindex = NULL,
  wt,
  df,
  method,
  group = NULL,
  exclude = NULL
)

repsetupILSA(
  study,
  year,
  repwt = NULL,
  repindex = NULL,
  df,
  group = NULL,
  exclude = NULL
)

Arguments

repwt

a string indicating the common names for the replicate weights columns (within df), or a data frame with the replicate weights.

repindex

a repweights.index object generated with repcreate(..., index = TRUE). Using this argument instead of repwt will speed up the estimations considerably.

wt

a string specifying the name of the column (within df) with the total weights.

df

a data frame.

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.

group

a string specifying the variable name (within df) to be used for grouping. Categories in group are treated as independent, e.g., countries.

exclude

a vector indicating which groups (in the same format as group) should be excluded from the pooled and composite estimates.

study

a string indicating the study name. For checking available studies use ILSAinfo$weights.

year

a numeric value indicating the study year. For checking available years use ILSAinfo$weights.

Value

a list to be used in other functions.

Examples

# Creation of replicate weights
RW <- repcreate(df = repdata, # the data frame with all the information
                 wt = "wt", # the total weights column name
                 jkzone = "jkzones", # the jkzones column name
                 jkrep = "jkrep", # the jkreps column name
                 repwtname = "REPWT", # the desired name for the rep weights
                 reps = 50, # the number of replications
                 method = "ICILS") # the name of the method aka the study name

### No groups ----
stp1 <- repsetup(repwt = RW, wt = "wt", df = repdata, method = "ICILS")
stp1
#> Error in get(x$repwt): object 'RW' not found

### Groups ----
stp2 <- repsetup(repwt = RW, wt = "wt", df = repdata, method = "ICILS",
                 group = "GROUP", exclude = "GR2")
stp2
#> Error in get(x$repwt): object 'RW' not found


### repmean ----

repmean(x = "Math1",setup = stp1)
#>      N    mean      se      sd    sdse     var   varse
#> 1 5000 0.00191 0.01718 1.02336 0.00928 1.04726 0.01899

repmean(x = "Math1",setup = stp2)
#>       group    N     mean      se      sd    sdse     var   varse
#> 1    Pooled 3334 -0.00267 0.02192 1.08611 0.01133 1.17964 0.02462
#> 2 Composite   NA -0.00327 0.01511 0.90647 0.01033 0.82169 0.01874
#> 3       GR1 1667 -0.60164 0.02193 0.90847 0.01330 0.82532 0.02416
#> 4       GR2 1666  0.01102 0.02383 0.88556 0.01507 0.78422 0.02668
#> 5       GR3 1667  0.59510 0.02079 0.90446 0.01582 0.81805 0.02865