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This data has two extra columns from the original `identity` data: `w` and `ranking`, which are respectively the estimated weights based on inverse probability weighting and the ranking pattern that the respondent provided, united into a single column.

Usage

identity_w

Format

## `identity_w` A data frame with 1,082 rows and 17 columns:

w

Estimated weight 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.

Source

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