Methods for Conducting Nonresponse Bias Analysis (NRBA)

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Documentation for package ‘nrba’ version 0.3.1

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assess_range_of_bias Assess the range of possible bias based on specified assumptions about how nonrespondents differ from respondents
calculate_response_rates Calculate Response Rates
chisq_test_ind_response Test the independence of survey response and auxiliary variables
chisq_test_vs_external_estimate Test of differences in survey percentages relative to external estimates
get_cumulative_estimates Calculate cumulative estimates of a mean/proportion
involvement_survey_pop Parent involvement survey: population data
involvement_survey_srs Parent involvement survey: simple random sample
involvement_survey_str2s Parent involvement survey: stratified, two-stage sample
predict_outcome_via_glm Fit a regression model to predict survey outcomes
predict_response_status_via_glm Fit a logistic regression model to predict response to the survey.
rake_to_benchmarks Re-weight data to match population benchmarks, using raking or post-stratification
stepwise_model_selection Select and fit a model using stepwise regression
t_test_by_response_status t-test of differences in means/percentages between responding sample and full sample, or between responding sample and eligible sample
t_test_of_weight_adjustment t-test of differences in estimated means/percentages from two different sets of replicate weights.
t_test_resp_vs_elig t-test of differences in means/percentages between responding sample and full sample, or between responding sample and eligible sample
t_test_resp_vs_full t-test of differences in means/percentages between responding sample and full sample, or between responding sample and eligible sample
t_test_vs_external_estimate t-test of differences in means/percentages relative to external estimates
wt_class_adjust Adjust weights in a replicate design for nonresponse or unknown eligibility status, using weighting classes