Identity-ranking data with estimated weights based on inverse probability weighting

This data is the `results` element returned by applying `imprr_weights()` to `identity`. It adds two columns to the original `identity` data: `weights`, the estimated inverse probability weights, and `ranking`, the pasted full ranking profile.

Usage

identity_w

Format

## `identity_w` A data frame with 1,082 rows and 18 columns:

weights: Estimated weights based on inverse probability weighting.
s_weight: Survey weight.
app_identity: Full ranking profile for the main identity ranking question.
app_identity_1: Marginal ranking for party (main identity ranking question).
app_identity_2: Marginal ranking for religion (main identity ranking question).
app_identity_3: Marginal ranking for gender (main identity ranking question).
app_identity_4: Marginal ranking for race (main identity ranking question).
anc_identity: Full ranking profile for the anchor ranking question.
anc_identity_1: Marginal ranking for household (anchor question).
anc_identity_2: Marginal ranking for neighborhood (anchor question).
anc_identity_3: Marginal ranking for city (anchor question).
anc_identity_4: Marginal ranking for state (anchor question).
anc_correct_identity: Whether the respondent answered the anchor questions correctly. This is a binary variable that 1 if the respondent correctly answers the anchor ranking question and 0 if otherwise.
app_identity_recorded: Recorded responses for the main identity ranking question.
anc_identity_recorded: Recorded responses for the anchor ranking question.
app_identity_row_rnd: The order in which the items were randomly presented for the respondent in the main ranking question.
anc_identity_row_rnd: The order in which the items were randomly presented for the respondent in the anchor ranking question.
ranking: Pasted full ranking profile reconstructed from the marginal ranking columns. In this dataset, it matches app_identity.

Source

<https://github.com/sysilviakim/ranking_error>