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pneumo = transform(pneumo, let = log(exposure.time))
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fit = vglm(cbind(normal, mild, severe) ~ let, multinomial, pneumo)
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99
fit = vglm(cbind(normal, mild, severe) ~ let,
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cumulative(reverse=TRUE, parallel=TRUE),
100
cumulative(reverse = TRUE, parallel = TRUE),
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mynewdata = with(pneumo, data.frame(let = let[ii]+hh))
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(newp <- predict(fit, newdata=mynewdata, type="response"))
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(newp <- predict(fit, newdata = mynewdata, type = "response"))
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# Compare the difference. Should be the same as hh --> 0.
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round(dig=3, (newp-fitted(fit)[ii,])/hh) # Finite-difference approximation
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round(dig=3, margeff(fit, subset=ii)["let",])
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round(dig = 3, (newp-fitted(fit)[ii,])/hh) # Finite-difference approximation
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round(dig = 3, margeff(fit, subset = ii)["let",])
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round(dig=3, margeff(fit))
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round(dig=3, margeff(fit, subset=2)["let",])
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round(dig=3, margeff(fit, subset=c(FALSE,TRUE))["let",,]) # recycling
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round(dig=3, margeff(fit, subset=c(2,4,6,8))["let",,])
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round(dig = 3, margeff(fit))
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round(dig = 3, margeff(fit, subset = 2)["let",])
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round(dig = 3, margeff(fit, subset = c(FALSE,TRUE))["let",,]) # recycling
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round(dig = 3, margeff(fit, subset = c(2,4,6,8))["let",,])