[R] predict.lm(...,type="terms") question

[Peter Ehlers]

I think that what the OP is looking for comes under the heading of
"inverse regression" or the "calibration" problem. One reference
with a simple explanation including confidence intervals is "Applied
regression analysis" by Draper and Smith. (It's in section 3.2 in
my 3rd edition).

Peter Ehlers

On 2012-08-29 10:03, Rui Barradas wrote:
> Hello,
>
> Inline.
> Em 29-08-2012 16:06, John Thaden escreveu:
>> Could it be that my newdata object needs to include a column for the
>> concn term even though I'm asking for concn to be predicted? If so,
>> what numbers would I fill it with? Or should my newdata object include
>> the original data, too? Is there another mailing list I can ask?
>
> stackoverflow.com
>
> There's an R tag.
>
> Rui Barradas
>> Thanks,
>> -John
>>
>> On Wed, Aug 29, 2012 at 9:16 AM, John Thaden <johnthaden at gmail.com> wrote:
>>> I think I may be misreading the help pages, too, but misreading how?
>>>
>>> I agree that inverting the fitted model is simpler, but I worry that I'm
>>> misusing ordinary least squares regression by treating my response, with its
>>> error distribution, as a predictor with no such error. In practice, with my
>>> real data that includes about six independent peak area measurements per
>>> known concentration level, the diagnostic plots from plot.lm(inv.model) look
>>> very strange and worrisome.
>>>
>>> Certainly predict.lm(..., type = "terms") must be able to do what I need.
>>>
>>> -John
>>>
>>> On Wed, Aug 29, 2012 at 6:50 AM, Rui Barradas <ruipbarradas at sapo.pt> wrote:
>>>> Hello,
>>>>
>>>> You seem to be misreading the help pages for lm and predict.lm, argument
>>>> 'terms'.
>>>> A much simpler way of solving your problem should be to invert the fitted
>>>> model using lm():
>>>>
>>>>
>>>> model <- lm(area ~ concn, data)  # Your original model
>>>> inv.model <- lm(concn ~ area, data = data)  # Your problem's model.
>>>>
>>>> # predicts from original data
>>>> pred1 <- predict(inv.model)
>>>> # predict from new data
>>>> pred2 <- predict(inv.model, newdata = new)
>>>>
>>>> # Let's see it.
>>>> plot(concn ~ area, data = data)
>>>> abline(inv.model)
>>>> points(data$area, pred1, col="blue", pch="+")
>>>> points(new$area, pred2, col="red", pch=16)
>>>>
>>>>
>>>> Also, 'data' is a really bad variable name, it's already an R function.
>>>>
>>>> Hope this helps,
>>>>
>>>> Rui Barradas
>>>>
>>>> Em 28-08-2012 23:30, John Thaden escreveu:
>>>>> 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?
>>>>>
>>>>> ______________________________________________
>>>>> R-help at r-project.org mailing list
>>>>> https://stat.ethz.ch/mailman/listinfo/r-help
>>>>> PLEASE do read the posting guide
>>>>> http://www.R-project.org/posting-guide.html
>>>>> and provide commented, minimal, self-contained, reproducible code.
>>>>
>
> ______________________________________________
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> PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
>