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nonprobsvy version 0.1.0
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@LukaszChrostowski LukaszChrostowski released this 09 Apr 18:27
· 32 commits to main since this release
v0.1.0
68c782e

Version of the package submitted to CRAN

nonprobsvy 0.1.0

  • implemented population mean estimation using doubly robust, inverse probability weighting and mass imputation methods
  • implemented inverse probability weighting models with Maximum Likelihood Estimation and Generalized Estimating Equations methods with logit, complementary log-log and probit link functions.
  • implemented generalized linear models, nearest neighbours and predictive mean matching methods for Mass Imputation
  • implemented y-yhat and yhat-yhat predictive mean matching
  • implemented bias correction estimators for doubly-robust approach
  • implemented estimation methods when vector of population means/totals is available
  • implemented variables selection with SCAD, LASSO and MCP penalization equations
  • implemented analytic and bootstrap (with parallel computation - doParallel package) variance for described estimators
  • added control parameters for models
  • added S3 methods for object of nonprob class such as
    • nobs for samples size
    • pop.size for population size estimation
    • residuals for residuals of the inverse probability weighting model
    • cooks.distance for identifying influential observations that have a significant impact on the parameter estimates
    • hatvalues for measuring the leverage of individual observations
    • logLik for computing the log-likelihood of the model,
    • AIC (Akaike Information Criterion) for evaluating the model based on the trade-off between goodness of fit and complexity, helping in model selection
    • BIC (Bayesian Information Criterion) for a similar purpose as AIC but with a stronger penalty for model complexity
    • confint for calculating confidence intervals around parameter estimates
    • vcov for obtaining the variance-covariance matrix of the parameter estimates
    • deviance for assessing the goodness of fit of the model

Unit tests

  • added unit tests for IPW estimators
  • added unit tests for MI estimators
  • added unit tests for DR estimators
  • added unit tests for variable selection models
  • Multicore tests will only be performed after TEST_NONPROBSVY_MULTICORE_DEVELOPER
    is set to "true" via Sys.setenv

Github repository

  • added automated R-cmd check
  • added CRAN and codecov badges

Documentation

  • added documentation for nonprob function
  • added documenation for control functions
  • added documentation for link functions

Full changelog: v0.1.0

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