Function to conduct a statistical test with the null hypothesis that there is no difference between the correlation coefficients between list experiment and endorsement experiment data.

comp.listEndorse(y.endorse, y.list, treat, n.draws = 10000, alpha = 0.05, endorse.mean = FALSE, method = "pearson")

y.endorse | A numerical matrix containing the response data for the endorsement experiment. |
---|---|

y.list | A numerical vector containing the response data for a list experiment. |

treat | A numerical vector containing the binary treatment status for the experiments. The treatment assignment must be the same for both experiments to compare across experiments. |

n.draws | Number of Monte Carlo draws. |

alpha | Confidence level for the statistical test. |

endorse.mean | A logical value indicating whether the mean endorsement experiment response is taken across questions. |

method | The method for calculating the correlation, either Pearson's rho or Kendall's tau. |

`comp.listEndorse`

returns a list with four elements: the
correlation statistic (rho or tau) for the treatment group as
`cor.treat`

, the correlation statistic for the control group as
`cor.control`

, the p.value for the statistical test comparing the two
correlation statistics as `p.value`

, and the bootstrapped confidence
interval of the difference as `ci`

.

This function allows the user to calculate the correlation between list and endorsement experiment data within the control group and the treatment group, and to conduct a statistical test with the null hypothesis of no difference between the two correlation coefficients.

Blair, Graeme, Jason Lyall and Kosuke Imai. (2014) ``Comparing and Combining List and Experiments: Evidence from Afghanistan." American Journal of Political Science. available at http://imai.princeton.edu/research/comp.html