Hey folks, Don't know if anyone else is trying to use the "weights" argument in Zelig. Sam and I are using weighted survey data to try to estimate an oprobit model. For one of the models we are estimating, when we run Zelig with a vector of observation weights entered, we get coefficient estimates that are very close to our author's, but our standard errors are extremely small (far smaller than the author's). We aren't sure why this is or how to correct the problem. For another very similar model, including a vector of weights just results in the following error message: zelig.us2 <- zelig(as.factor(jobcomm) ~ demid + repid + hhunion + female + nonwhite + income + educ + educinc + age + hhlayoffs + ncentral + south + west, model="oprobit", weights=starting2$weight, data=starting2) Error in function (formula, data, weights, start, ..., subset, na.action, : attempt to find suitable starting values failed In addition: Warning messages: 1: In glm.fit(X, y1, wt, family = binomial("probit"), offset = offset) : algorithm did not converge 2: In glm.fit(X, y1, wt, family = binomial("probit"), offset = offset) : fitted probabilities numerically 0 or 1 occurred If anyone has any thoughts as to what might be going on, we would love to hear them. Thanks for your help, Kyle _______________________________________________ gov2001-l mailing list gov2001-l at lists.fas.harvard.edu http://lists.fas.harvard.edu/mailman/listinfo/gov2001-l