## Assessing punitive damages and adjusting census counts: a hierarchical Bayesian approach |

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3.6 with clusters Adjusting the Census amount of punitive Analysis of Variance assumption award punitive damages Census Adjustment census counts civil trials clusters defined compensatory damages covariance matrix covariates linking damages are awarded decision to award differential undercount dual systems Dual-Systems Estimator Effects Conditional Modes Eisenberg equation errors estimated coefficient Figure Fixed Effects Estimates Freedman Heckman model hierarchical linear model hierarchical logistic model hierarchical model hierarchical regression Icsty individual is suing juries likelihood function ln(compensatory damages logarithm of compensatory logarithm of punitive LOGCOMP LOGCOMP LOGCOMP logpercapita Marginal Likelihood MlNlTAB ANOVA output natural logarithm normally distributed number of fish output for model p-value PDCOMBO plaintiff/defendant combination poststrata probability that punitive probit model punitive damage awards punitive damages versus Random Effects Conditional raw adjustment factor regional variation regression model Residual Variance Restricted AIC S-Plus output statistically significant suing a business systems estimator total number variable AVLOGCOMP versus the natural Wachter