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 <mtb...@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. 538...@gmail.com ______________________________________________ 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.
