| sumData {ramchoice} | R Documentation |
Generate Summary Statistics
Description
sumData generates summary statistics. Given a collection of
choice problems and corresponding choices, sumData calculates the
number of occurrences of each choice problem, as well as the empirical choice
probabilities.
This function is embedded in revealPref.
Usage
sumData(menu, choice)
Arguments
menu |
Numeric matrix of 0s and 1s, the collection of choice problems. |
choice |
Numeric matrix of 0s and 1s, the collection of choices. |
Value
sumMenu |
Summary of choice problems, with repetitions removed. |
sumProb |
Estimated choice probabilities as sample averages for different choice problems. |
sumN |
Effective sample size for each choice problem. |
sumMsize |
Size of each choice problem. |
sumProbVec |
Estimated choice probabilities as sample averages, collapsed into a column vector. |
Sigma |
Estimated variance-covariance matrix for the choice rule, scaled by relative sample sizes. |
Author(s)
Matias D. Cattaneo, Princeton University. cattaneo@princeton.edu.
Paul Cheung, University of Maryland. hycheung@umd.edu
Xinwei Ma (maintainer), University of California San Diego. x1ma@ucsd.edu
Yusufcan Masatlioglu, University of Maryland. yusufcan@umd.edu
Elchin Suleymanov, Purdue University. esuleyma@purdue.edu
References
M. D. Cattaneo, X. Ma, Y. Masatlioglu, and E. Suleymanov (2020). A Random Attention Model. Journal of Political Economy 128(7): 2796-2836. doi:10.1086/706861
M. D. Cattaneo, P. Cheung, X. Ma, and Y. Masatlioglu (2024). Attention Overload. Working paper.
Examples
# Load data
data(ramdata)
# Generate summary statistics
summaryStats <- sumData(ramdata$menu, ramdata$choice)
nrow(summaryStats$sumMenu)
min(summaryStats$sumN)
summaryStats$sumMenu[1, ]
summaryStats$sumProb[1, ]
summaryStats$sumN[1]