R help - Jan 2014 - Predicting probabilities from a logistic regression by hand (in code)

Thanks for looking at this, I've been tearing my hair out for a day or so
now.

I have done a multiple variable logistic regression in R, and obtained my
coefficients. I am able to make predictions for the training data in R
without problem. But now I would like to create a prediction model in Ruby
(that was the original point of doing the regression) and I'm having some
trouble.

Basically, my equation is:

predicted_logit = K + v1*c1 + v2*c2 + ... vn*cn
odds_ratio = e^predicted_logit/(1+e^predicted_logit)

But it always seems to either give 1.0 or 0.0! The output of predict() in R
is generally something nice and soft like 0.5578460!

I realize not everyone knows Ruby, but I'll include my code here for
reference:

# These are the coefficients that R gives me from my logistic regression:
intercept = 0.2700309

coefficients = {
  high: 1.0136028, 
  low: 1.0016712, 
  germ_mean: 1.0233327,
  gdds: 0.9990283,
  early_gdds: 0.9986464,
  mid_gdds: 1.0002979,
  late_gdds: 0
}

# And this is what R predicts for one datum:
#
#   outcome high low germ_mean gdds early_gdds mid_gdds late_gdds p_success
# 1       1   73  28        40  119          0       91        28 0.5578460
# ...

# So to get my own p_success, first I multiply each coefficient by it's
input data
period = {:high=>73, :low=>28, :germ_mean=>40, :gdds=>119,
:early_gdds=>0,
:mid_gdds=>91, :late_gdds=>28}
products = coefficients.map {|name,value| period[name]*value }

# Then I add those together and add that to the intercept
predicted_logit = intercept + products.sum

# Then my probability should be e^predicted_logit over 1 +
e^predicted_logit:
odds_ratio = Math.exp(predicted_logit) / (1 + Math.exp(predicted_logit))

# But the odds ratio comes out as 1.0, not 0.5578460 like R predicts.



--
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Sent from the R help mailing list archive at Nabble.com.

On Jan 16, 2014, at 6:53 PM, erikpukinskis wrote:
> Thanks for looking at this, I've been tearing my hair out for a day or
so
> now.
> 
> I have done a multiple variable logistic regression in R, and obtained my
> coefficients. I am able to make predictions for the training data in R
> without problem. But now I would like to create a prediction model in Ruby
> (that was the original point of doing the regression) and I'm having
some
> trouble.
> 
> Basically, my equation is:
> 
> predicted_logit = K + v1*c1 + v2*c2 + ... vn*cn
> odds_ratio = e^predicted_logit/(1+e^predicted_logit)
> 
> But it always seems to either give 1.0 or 0.0! The output of predict() in R
> is generally something nice and soft like 0.5578460!
> 
> I realize not everyone knows Ruby, but I'll include my code here for
> reference:
> 
> # These are the coefficients that R gives me from my logistic regression:
> intercept = 0.2700309
> 
> coefficients = {
>  high: 1.0136028, 
>  low: 1.0016712, 
>  germ_mean: 1.0233327,
>  gdds: 0.9990283,
>  early_gdds: 0.9986464,
>  mid_gdds: 1.0002979,
>  late_gdds: 0
> }
If you are going to write ruby code, then why post to an R mailing list? 

-- 
David.
> 
> # And this is what R predicts for one datum:
> #
> #   outcome high low germ_mean gdds early_gdds mid_gdds late_gdds p_success
> # 1       1   73  28        40  119          0       91        28 0.5578460
> # ...
> 
> # So to get my own p_success, first I multiply each coefficient by it's
> input data
> period = {:high=>73, :low=>28, :germ_mean=>40, :gdds=>119,
:early_gdds=>0,
> :mid_gdds=>91, :late_gdds=>28}
> products = coefficients.map {|name,value| period[name]*value }
> 
> # Then I add those together and add that to the intercept
> predicted_logit = intercept + products.sum
> 
> # Then my probability should be e^predicted_logit over 1 +
> e^predicted_logit:
> odds_ratio = Math.exp(predicted_logit) / (1 + Math.exp(predicted_logit))
> 
> # But the odds ratio comes out as 1.0, not 0.5578460 like R predicts.
> 
> 
> 
> --
> View this message in context:
http://r.789695.n4.nabble.com/Predicting-probabilities-from-a-logistic-regression-by-hand-in-code-tp4683713.html
> Sent from the R help mailing list archive at Nabble.com.
> 
> ______________________________________________
> 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.
David Winsemius
Alameda, CA, USA