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lsasim (version 2.1.4)

Functions to Facilitate the Simulation of Large Scale Assessment Data

Description

Provides functions to simulate data from large-scale educational assessments, including background questionnaire data and cognitive item responses that adhere to a multiple-matrix sampled design. The theoretical foundation can be found on Matta, T.H., Rutkowski, L., Rutkowski, D. et al. (2018) .

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Version

Install

install.packages('lsasim')

Monthly Downloads

212

Version

2.1.4

License

GPL-3

Maintainer

Waldir Leoncio

Last Published

August 22nd, 2023

Functions in lsasim (2.1.4)

calc_replicate_weights

Calculate replicate weights and summary statistics

Calculate Standard Error of Intraclass Correlation

Generate replicates of a dataset using Balanced Repeated Replication

Assignment of test items to blocks

Generation of random correlation matrix

Generation of covariance matrices

Assignment of item blocks to test booklets

calc_var_within

Calculate variance within classes

calc_var_between

Calculate variance between classes

check_ignored_parameters

Checks if provided parameters are ignored

Simulate item responses from an item response model

Calculate the total variance

Randomly generate a matrix of factor loadings

check_condition

Check if an error condition is satisfied

check_n_N_class

Check class of n or N

Assignment of test booklets to test takers

lsasim: A package for simulating large scale assessment data

cluster_message

Print messages about clusters

pisa2012_math_block

PISA 2012 mathematics item - item block indicator matrix

check_valid_structure

Check if List is Valid

anova.lsasimcluster

Generate an ANOVA table for LSASIM clusters

Generation of item parameters from uniform distributions

pisa2012_math_booklet

PISA 2012 mathematics item block - test booklet indicator matrix

convert_vector_to_list

Convert Vector to Expanded List

Generate cluster sample

Defines vector as range

Generate analytical covariance matrix

attribute_cluster_labels

Attribute Labels in Hierarchical Structure

customize_summary

Customize Summary

Print the ANOVA table

Generate latent regression covariance matrix

Generation of random cumulative proportions

gen_X_W_cluster

Generate n_X and n_W for clusters

pisa2012_math_item

Item parameter estimates for 2012 PISA mathematics assessment

questionnaire_gen_family

Generation of ordinal and continuous variables

recalc_final_weights

Recalculate final weights

cluster_gen_separate

Generate cluster samples with individual questionnaires

Generates cat_prop for questionnaire_gen

Dataset summary statistics

sample_within_range

Sample from range

cluster_gen_together

Generate cluster samples with lowest-level questionnaires

Transform regular vector into selection vector

pisa2012_q_cormat

Correlation matrix from the PISA 2012 background questionnaire

Prints welcome message on package load

validate_questionnaire_gen

Wrapper-functions for check_condition

questionnaire_gen_polychoric

Generation of ordinal and continuous variables

draw_cluster_structure

Draw Cluster Structure

Setup full YXW covariance matrix

weight_responses

Weight responses

Randomly generate the quantity of background variables

Intraclass correlation

Generate replicates of a dataset using Jackknife

pt_bis_conversion

Analytical point-biserial conversion

label_respondents

Label respondents

pisa2012_q_marginal

Marginal proportions from the PISA 2012 background questionnaire

questionnaire_gen

Generation of ordinal and continuous variables

Pluralize words

Sampling variance of the mean for replications

Generate data from a Zero-truncated Poisson

Generation of item response data using a rotated block design

whitelist_message

Whitelist message

Sample from population structure

Split variables in cat_prop

summary.lsasimcluster

Summarizes clusters

Generate regression coefficients