search for: afactorimpacts

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2007 May 10
1
Follow-up about ordinal logit with mixtures: how about 'continuation ratio' strategy?
...# linear predictor ### eta = 0.3 * x + 0 (afactor==1)+ 0.4 * (afactor==2) + 0.5 (afactor==3)+ 0.9 (afactor==4) ### and the "cutpoints" between categories are -2.3, -0.5, and 0.66. N <- 1000 A <- -1 B <- 0.3 cutpoint <- c( -2.3, -0.5, 0.66 ) afactor <- gl (n=4, k = N/4) afactorImpacts <- c( 0, 0.4, .5, .9 ) ### Make "first" impact 0 so it does not confuse our study of intercept & cutpoints. ### Any other value gets up getting added into the intercept and/or first cutpoint. set.seed(333) x <- 1 + 10 * rnorm(N) eta <- B * x + afactorImpacts[as.numeric(afa...