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Need to replicate Boltzman Signmodial Curve fit from Graph Pad

You may want to compare R's four point logistic with the results you get
using Graphpad. For these data the Bottom parameter is not significantly
different from zero (so the three point sigmoid might be adequate), but as
Bert points out, especially with only 8 data points, it is probably
overfitting the model.
+ 3.8 968
+ 5.0 1347
+ 5.8 2867
+ 6.6 9203
+ 7.0 15817
+ 7.4 20297
+ 8.2 31916
+ 9.2 35756",
+ header=TRUE)
Formula: counts ~ SSfpl(pH, Bottom, Top, V50, Slope)

Parameters:
          Estimate  Std. Error t value     Pr(>|t|)    
Bottom   718.76871   579.25327   1.241     0.282463    
Top    36983.98871  1008.31727  36.679 0.0000032986 ***
V50        7.24930     0.05054 143.436 0.0000000142 ***
Slope      0.55582     0.05023  11.065     0.000379 ***
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

Residual standard error: 767.1 on 4 degrees of freedom

Number of iterations to convergence: 0 
Achieved convergence tolerance: 0.000003808
Waiting for profiling to be done...
                2.5%         97.5%
Bottom  -963.4106068  2243.7154750
Top    34499.9962176 40150.4114887
V50        7.1173103     7.4033391
Slope      0.4382893     0.7114438
Bottom           Top           V50         Slope 
  718.7687104 36983.9887074     7.2493032     0.5558236
-------------------------------------
David L Carlson
Associate Professor of Anthropology
Texas A&M University
College Station, TX 77840-4352

-----Original Message-----
From: r-help-bounces at r-project.org [mailto:r-help-bounces at r-project.org] On
Behalf Of Bert Gunter
Sent: Tuesday, April 23, 2013 12:04 PM
To: John Kane
Cc: r-help at r-project.org; J J
Subject: Re: [R] Need to replicate Boltzman Signmodial Curve fit from Graph
Pad

I think you'll find that this is just an alternate parameterization of a 4 P
logistic.
... and in any case there is no statistically detectable difference between
the two.

That is, this is just basically a Graphpad marketing ploy. Fit such data
with anyone's logistic function ... and that is probably overfitting in many
cases, anyway.

Cheers,
Bert
On Tue, Apr 23, 2013 at 9:54 AM, John Kane <jrkrideau at inbox.com> wrote:
grateful.