Hello all,
How do I actually use the output of predict.lm(..., type="terms") to
predict new term values from new response values?
I'm a chromatographer trying to use R (2.15.1) for one of the most
common calculations in that business:
- Given several chromatographic peak areas measured for control
samples containing a molecule at known (increasing) concentrations,
first derive a linear regression model relating the known
concentration (predictor) to the observed peak area (response)
- Then, given peak areas from new (real) samples containing
unknown amounts of the molecule, use the model to predict
concentrations of the
molecule in the unknowns.
In other words, given y = mx +b, I need to solve x' = (y'-b)/m for new data y'
and in R, I'm trying something like this
require(stats)
data <- data.frame(area = c(4875, 8172, 18065, 34555), concn = c(25,
50, 125, 250))
new <- data.frame(area = c(8172, 10220, 11570, 24150))
model <- lm(area ~ concn, data)
pred <- predict(model, type = "terms")
#predicts from original data
pred <- predict(model, type = "terms", newdata = new)
#error
pred <- predict(model, type = "terms", newdata = new, se.fit = TRUE)
#error
pred <- predict(model, type = "terms", newdata = new, interval =
"prediction") #error
new2 <- data.frame(area = c(8172, 10220, 11570, 24150), concn = 0)
new2
pred <- predict(model, type = "terms", newdata = new2)
#wrong results
Can someone please show me what I'm doing wrong?
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