Rrepest {Rrepest}

Rrepest

Description

Estimates statistics using replicate weights (Balanced Repeated Replication (BRR) weights, Jackknife replicate weights,...), thus accounting for complex survey designs in the estimation of sampling variances. It is specially designed to be used with the data sets produced by the Organization for Economic Cooperation and Development (OECD), some of which include the Programme for International Student Assessment (PISA) and Teaching and Learning International Survey (TALIS) data sets, but works for all International Large Scale Assessments that use replicated weights. It also allows for analyses with multiply imputed variables (plausible values); where plausible values are included in a pvvarlist, the average estimator across plausible values is reported and the imputation error is added to the variance estimator.

Usage

Rrepest(
  data,
  svy,
  est,
  by = NULL,
  over = NULL,
  test = FALSE,
  user_na = FALSE,
  show_na = FALSE,
  flag = FALSE,
  fast = FALSE,
  tabl = FALSE,
  average = NULL,
  group = NULL,
  ...
)

Arguments

data

(dataframe) df to analyze

svy

(string) Possible projects to analyse.must be equal to ALL, IALS, IELS, PIAAC, PISA, PISA2015, PISAOOS, TALISSCH, TALISTCH .

est

(est function) that takes arguments stimate, target variable, regressor (optional for linear regressions)

by

(string vector) column in which we'll break down results

over

(vector string) columns over which to do analysis

test

(bool) TRUE: will calculate the difference between over variables

user_na

(bool) TRUE: show nature of user defined missing values for by.var

show_na

(bool) TRUE: include na in frequencies of x

flag

(bool) TRUE: Show NaN when there is not enough cases (or schools)

fast

(bool) TRUE: Only do 6 replicated weights

tabl

(bool) TRUE: Creates a flextable with all examples

average

(grp function) that takes arguments group.name, column, cases to create averages at the end of df

group

(grp function) that takes arguments group.name, column, cases to create groups at the end of df

...

Optional filtering parameters: i.e.: isced = 2, n.pvs = 5, cm.weights = c("finw",paste0("repw",1:22)) var.factor = 1/(0.5^2) z.score = qnorm(1-0.05/2)

Value

Dataframe containing estimation "b." and standard error "se." of desired processes

Examples

data(df_pisa18)

Rrepest(data = df_pisa18,
svy = "PISA2015",
est = est("mean","AGE"),
by = c("CNT"))