On 25/04/12 02:17, Mark Na wrote:
> Hi Greg. Thanks for your reply. Do you know if there is a way to use the
> confint function to get a p-value on this test?
In general it is at least *roughly* true that one rejects H_0: theta = 
theta_0
vs. H_a: theta != theta_0 at significance level alpha if and only if theta_0
is *not* within a 100*(1-alpha) percent confidence interval for theta.

HTH

     cheers,

         Rolf Turner
> Thanks, Mark
>
>
> On Mon, Apr 23, 2012 at 3:10 PM, Greg Snow<538280@gmail.com>  wrote:
>
>> One option is to subtract the continuous variable from y before doing
>> the regression (this works with any regression package/function).  The
>> probably better way in R is to use the 'offset' function:
>>
>> formula = I(log(data$AB.obs + 1, 10)-log(data$SIZE,10)) ~
>> log(data$SIZE, 10) + data$Y
>> formula = log(data$AB.obs + 1) ~ offset( log(data$SIZE,10) ) +
>> log(data$SIZE,10) + data$Y
>>
>> Or you can use a function like 'confint' to find the confidence
>> interval for the slope and see if 1 is in the interval.
>>
>> On Mon, Apr 23, 2012 at 12:11 PM, Mark Na<mtb954@gmail.com>  wrote:
>>> Dear R-helpers,
>>>
>>> I would like to test if the slope corresponding to a continuous variable
>> in
>>> my model (summary below) is different than one.
>>>
>>> I would appreciate any ideas for how I could do this in R, after having
>>> specified and run this model?
>>>
>>> Many thanks,
>>>
>>> Mark Na
>>>
>>>
>>>
>>> Call:
>>> lm(formula = log(data$AB.obs + 1, 10) ~ log(data$SIZE, 10) +
>>>    data$Y)
>>>
>>> Residuals:
>>>     Min       1Q   Median       3Q      Max
>>> -0.94368 -0.13870  0.04398  0.17825  0.63365
>>>
>>> Coefficients:
>>>                   Estimate Std. Error t value  Pr(>|t|)
>>> (Intercept)        -1.18282    0.09120 -12.970<  2e-16 ***
>>> log(data$SIZE, 10)  0.56009    0.02564  21.846<  2e-16 ***
>>> data$Y2008          0.16825    0.04366   3.854  0.000151 ***
>>> data$Y2009          0.20310    0.04707   4.315 0.0000238 ***
>>> ---
>>> Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
>>>
>>> Residual standard error: 0.2793 on 228 degrees of freedom
>>> Multiple R-squared: 0.6768,     Adjusted R-squared: 0.6726
>>> F-statistic: 159.2 on 3 and 228 DF,  p-value:<  2.2e-16
>>>
>>>         [[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.
>>>
>>
>>
>> --
>> Gregory (Greg) L. Snow Ph.D.
>> 538280@gmail.com
>>
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>
>
>
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