# Create a randomized response design

Produces a (forced) randomized response design that measures the share of individuals with a given trait `prevalence_trait`

in a population of size `N`

. Probability of forced response ("Yes") is given by `prob_forced_yes`

, and rate at which individuals with trait lie is given by `withholding_rate`

.

randomized_response_designer(N = 1000, prob_forced_yes = 0.6, prevalence_rate = 0.1, withholding_rate = 0.5, args_to_fix = NULL)

## Arguments

N | An integer. Size of sample. |
---|---|

prob_forced_yes | A number in [0,1]. Probability of a forced yes. |

prevalence_rate | A number in [0,1]. Probability that individual has the sensitive trait. |

withholding_rate | A number in [0,1]. Probability that an individual with the sensitive trait hides it. |

args_to_fix | A character vector. Names of arguments to be args_to_fix in design. |

## Value

A randomized response design.

## Details

`randomized_response_designer`

employs a specific variation of randomized response designs in which respondents are required to report a args_to_fix answer to the sensitive question with a given probability (see Blair, Imai, and Zhou (2015) for alternative applications and estimation strategies).

See vignette online.

## Examples

# Generate a randomized response design using default arguments: randomized_response_design <- randomized_response_designer()