Authors
Citation
-Source: DESCRIPTION
Source: DESCRIPTION
Chrostowski Ł, Beręsewicz M (2024).
nonprobsvy: Inference Based on Non-Probability Samples.
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Complementary log-log model for weights adjustment
- Source: R/cloglogModel.R
+ Source: R/cloglogModel.R
cloglog_model_nonprobsvy.Rd
Confidence Intervals for Model Parameters
- Source: R/simple_methods.R
+ Source: R/simple_methods.R
confint.nonprobsvy.Rd
Control parameters for inference
- Source: R/control_inference.R
+ Source: R/control_inference.R
controlInf.Rd
Control parameters for outcome model
- Source: R/control_outcome.R
+ Source: R/control_outcome.R
controlOut.Rd
Control parameters for selection model
- Source: R/control_selection.R
+ Source: R/control_selection.R
controlSel.Rd
Logit model for weights adjustment
- Source: R/logitModel.R
+ Source: R/logitModel.R
logit_model_nonprobsvy.Rd
Inference with the non-probability survey samples
- Source: R/main_function_documentation.R
, R/nonprob.R
+ Source: R/main_function_documentation.R
, R/nonprob.R
nonprob.Rd
Probit model for weights adjustment
- Source: R/probitModel.R
+ Source: R/probitModel.R
probit_model_nonprobsvy.Rd
Summary statistics for model of nonprobsvy class.
- Source: R/summary.R
+ Source: R/summary.R
summary.nonprobsvy.Rd
Obtain Covariance Matrix estimation.
- Source: R/simple_methods.R
+ Source: R/simple_methods.R
vcov.nonprobsvy.Rd