Hi Albyn, Not a problem :)
I had calculated the CI using >confint(Regression_PhyloContrasts, level=0.95) Is that adequate? I had been using this as my indicator of significance, but ultimately I need a P-value for the deviation from a slope of 1. Which is where I ran into trouble trying to use offset( ) to change the default assumption of the linear model. Cat On Sat, Nov 24, 2012 at 11:52 PM, Albyn Jones <jo...@reed.edu> wrote: > Dear Cat > > My apologies for presuming... > > Here's a "primitive" solution: compute a t-statistic or CI. > > t = (beta-hat - 1)/SE(beta-hat), compare to qt(.975, res.df) > > Or Better, compute the 95% confidence interval > > beta-hat + c(-1,1)*qt(.975, res.df)*SE(beta-hat) > > albyn > > > On 2012-11-24 18:05, Catriona Hendry wrote: > >> Hi, >> >> @ Albyn, David.. No, its not homework. Its basic groundwork for testing >> allometric relationships for a graduate project I am working on. I read >> the >> guide before posting, I spent half the day trying to understand how I am >> going wrong based on the advice given to others. >> >> @Bert, David... I apologise for the lack of code, I wasn't sure how to >> explain my problem and I guess I went about it the wrong way. >> >> I do think this is what I need to be doing, I am testing allometric >> relationships of body size against a predicted isometric (1:1) >> relationship. So I would like to know if the relationship between my >> variables deviates from that. >> >> Hopefully the information below will be what is needed. >> >> Here is the part of the code relevant to the regression and plot: >> >> >> plot(Contrast_log_MTL_ALL, Contrast_log_FTL_ALL) >>> >> >> Regression_PhyloContrasts_ALL <- lm(Contrast_log_FTL_ALL ~ >>> >> Contrast_log_MTL_ALL, offset=1*Contrast_log_MTL_ALL) >> abline(Regression_**PhyloContrasts_ALL) >> >> the plot that resulted is attached as an image file. >> >> >> Below are the vectors of my variables. The are converted from other values >> imported and indexed from a csv file, so unfortunately I don't have matrix >> set up for them. >> >> Contrast_log_FTL_ALL Contrast_Log_MTL_ALL 83 0.226593 0.284521 84 >> 0.165517 0.084462 85 -0.1902 -0.0055 86 0.585176 0.639916 87 -0.01078 >> 0.118011 88 0.161142 0.073762 89 -0.08566 -0.04788 90 -0.13818 -0.0524 >> 91 -0.02504 -0.21099 92 -0.05027 -0.07594 93 -0.11399 -0.07251 94 >> -0.07299 -0.08247 95 -0.09507 -0.04817 96 0.207591 0.151695 97 -0.14224 >> -0.05097 98 0.06375 -0.0229 99 0.04607 0.06246 100 0.257389 0.190531 >> 101 >> -0.0612 -0.10902 102 -0.1981 -0.24698 103 -0.12328 -0.36942 104 >> 0.269877 >> 0.341989 105 0.125377 0.227183 106 0.087038 -0.05962 107 0.114929 >> 0.096112 108 0.252807 0.305583 109 -0.0895 -0.08586 110 -0.38483 >> -0.20671 >> 111 -0.72506 -0.63785 112 -0.37212 -0.21458 113 0.010348 0.117577 114 >> -0.09625 -0.0059 115 -0.26291 -0.25986 116 0.056922 0.064041 117 >> 0.051472 >> -0.09747 118 -0.05691 0.075005 119 0.117095 -0.15497 120 -0.01329 >> -0.12473 121 0.098725 0.020522 122 -0.0019 -0.01998 123 -0.12446 >> -0.02312 >> 124 0.019234 0.031391 125 0.385366 0.391766 126 0.495518 0.468946 127 >> -0.09251 -0.08045 128 0.147965 0.139117 129 -0.03143 -0.02319 130 >> -0.19801 -0.14924 131 0.014104 -0.01917 132 0.031872 -0.01381 133 >> -0.01412 -0.04381 134 -0.12864 -0.08527 135 -0.07179 -0.03525 136 >> 0.31003 >> 0.29553 137 -0.09347 -0.11903 138 -0.10706 -0.16654 139 0.078655 >> 0.065509 >> 140 0.08279 -0.00766 141 0.181885 0.001414 142 0.345818 0.496323 143 >> 0.235044 0.095073 144 -0.03022 0.039918 145 0.042577 0.136586 146 >> 0.064208 0.001379 147 -0.02237 -0.03009 148 -3.55E-05 0.040197 149 >> 0.011168 0.087116 150 0.019964 0.071822 151 -0.04602 -0.06616 152 >> 0.083087 0.038592 153 0.032078 0.107237 154 -0.21108 -0.22347 155 >> 0.122959 0.297917 156 -0.05898 0.012547 157 -0.07584 -0.21588 158 >> -0.00929 -0.06864 159 -0.01211 -0.04559 160 0.090948 0.136582 161 >> 0.016974 0.018259 162 -0.04083 0.016245 163 -0.20328 -0.31678 >> >> >> >> >> >> >> On Sat, Nov 24, 2012 at 8:22 PM, Bert Gunter <gunter.ber...@gene.com> >> wrote: >> >> 1. The model is correct : lm( y~ x + offset(x)) >>> ( AFAICS) >>> >>> 2. Read the posting guide, please: Code? I do not know what you mean by: >>> >>> " this resulted in a regression line that was plotted perpendicular to >>> the data when added with the abline function." >>> >>> Of course, maybe someone else will groc this. >>> >>> 3. I wonder if you really want to do what you are doing, anyway. For >>> example, in comparing two assays to see whether they give "similar" >>> results, you would **not** do what you are doing. If you care to follow >>> up >>> on this, I suggest you post complete context to a statistical mailing >>> list, >>> not here, like stats.stackexchange .com. Also, feel free to ignore me, >>> of >>> course. I'm just guessing. >>> >>> Cheers, >>> Bert >>> >>> Cheers, >>> Bert >>> >>> >>> On Sat, Nov 24, 2012 at 4:27 PM, Catriona Hendry <hen...@gwmail.gwu.edu >>> >wrote: >>> >>> Hi! >>>> >>>> I have a question that is probably very basic, but I cannot figure out >>>> how >>>> to do it. I simply need to compare the significance of a regression >>>> slope >>>> against a slope of 1, instead of the default of zero. >>>> >>>> I know this topic has been posted before, and I have tried to use the >>>> advice given to others to fix my problem. I tried the offset command >>>> based >>>> on one of these advice threads as follows: >>>> >>>> Regression <- lm(y~x+offset(1*x)) >>>> >>>> but this resulted in a regression line that was plotted perpendicular to >>>> the data when added with the abline function. >>>> >>>> I would be extremely grateful for your help!! >>>> >>>> Thanks!! >>>> >>>> Cat >>>> >>>> [[alternative HTML version deleted]] >>>> >>>> ______________________________**________________ >>>> R-help@r-project.org mailing list >>>> https://stat.ethz.ch/mailman/**listinfo/r-help<https://stat.ethz.ch/mailman/listinfo/r-help> >>>> PLEASE do read the posting guide >>>> http://www.R-project.org/**posting-guide.html<http://www.R-project.org/posting-guide.html> >>>> and provide commented, minimal, self-contained, reproducible code. >>>> >>>> >>> >>> >>> -- >>> >>> Bert Gunter >>> Genentech Nonclinical Biostatistics >>> >>> Internal Contact Info: >>> Phone: 467-7374 >>> Website: >>> >>> >>> http://pharmadevelopment.**roche.com/index/pdb/pdb-** >>> functional-groups/pdb-**biostatistics/pdb-ncb-home.htm<http://pharmadevelopment.roche.com/index/pdb/pdb-functional-groups/pdb-biostatistics/pdb-ncb-home.htm> >>> >>> >>> >>> > ______________________________**________________ > R-help@r-project.org mailing list > https://stat.ethz.ch/mailman/**listinfo/r-help<https://stat.ethz.ch/mailman/listinfo/r-help> > PLEASE do read the posting guide http://www.R-project.org/** > posting-guide.html <http://www.R-project.org/posting-guide.html> > and provide commented, minimal, self-contained, reproducible code. > -- ----------------------------------------- *Catriona Hendry* *Postgraduate Student* *Biological Sciences Department* *George Washington University* *hen...@gwmail.gwu.edu* [[alternative HTML version deleted]] ______________________________________________ R-help@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.
