Re: [R] Comparing each level of a factor to the global mean
You could subtract the mean from the response before fitting, then fit a model without an intercept. That would give you four parameters (one for each level) relative to the mean ... summary(lm(weight-mean(weight) ~ Diet -1, ChickWeight)) Jean On Thu, Jun 27, 2013 at 5:47 PM, Shaun Jackman sjack...@gmail.com wrote: Hi Jean, contr.treatment(4) shows what the default contrast matrix looks like for a factor with 4 levels. What function do I use to create a contrast matrix to compare each level with the global mean (four comparisons in total), and produce a table similar to `summary.lm`? Thanks, Shaun On 26 June 2013 05:50, Adams, Jean jvad...@usgs.gov wrote: Shaun, See the help on contrasts ... ?contr.treatment Jean On Tue, Jun 25, 2013 at 7:07 PM, Shaun Jackman sjack...@gmail.com wrote: Hi, I've used `lm` to create a linear model of a continuous variable against a factor variable with four levels using an example R data set (see below). By default, it uses a treatment contrast matrix that compares each level of the factor variable with the first reference level (three comparisons in total). I'd like to compare each level with the global mean (four comparisons in total), and produce a table similar to `summary.lm`. How do I go about this? ```r model - lm(weight ~ Diet, ChickWeight) summary(model) ``` Thanks, Shaun __ 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. [[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.
Re: [R] Comparing each level of a factor to the global mean
Hi Jean, contr.treatment(4) shows what the default contrast matrix looks like for a factor with 4 levels. What function do I use to create a contrast matrix to compare each level with the global mean (four comparisons in total), and produce a table similar to `summary.lm`? Thanks, Shaun On 26 June 2013 05:50, Adams, Jean jvad...@usgs.gov wrote: Shaun, See the help on contrasts ... ?contr.treatment Jean On Tue, Jun 25, 2013 at 7:07 PM, Shaun Jackman sjack...@gmail.com wrote: Hi, I've used `lm` to create a linear model of a continuous variable against a factor variable with four levels using an example R data set (see below). By default, it uses a treatment contrast matrix that compares each level of the factor variable with the first reference level (three comparisons in total). I'd like to compare each level with the global mean (four comparisons in total), and produce a table similar to `summary.lm`. How do I go about this? ```r model - lm(weight ~ Diet, ChickWeight) summary(model) ``` Thanks, Shaun __ 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. __ 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.
Re: [R] Comparing each level of a factor to the global mean
On Jun 27, 2013, at 3:47 PM, Shaun Jackman wrote: Hi Jean, contr.treatment(4) shows what the default contrast matrix looks like for a factor with 4 levels. What function do I use to create a contrast matrix to compare each level with the global mean (four comparisons in total), and produce a table similar to `summary.lm`? I believe you asking for contr.sum although I think there might be some differences between how it operates and what you are expressing as your expectations. contrasts(ChickWeight$Diet) - contr.sum(4) model - lm(weight ~ Diet, ChickWeight) summary(model) Call: lm(formula = weight ~ Diet, data = ChickWeight) Residuals: Min 1Q Median 3Q Max -103.95 -53.65 -13.64 40.38 230.05 Coefficients: Estimate Std. Error t value Pr(|t|) (Intercept) 125.869 2.986 42.150 2e-16 *** Diet1-23.223 4.454 -5.214 2.59e-07 *** Diet2 -3.252 5.380 -0.604 0.54576 Diet3 17.081 5.380 3.175 0.00158 ** --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 Residual standard error: 69.33 on 574 degrees of freedom Multiple R-squared: 0.05348, Adjusted R-squared: 0.04853 F-statistic: 10.81 on 3 and 574 DF, p-value: 6.433e-07 mean(ChickWeight$weight) [1] 121.8183 table(ChickWeight$Diet) 1 2 3 4 220 120 120 118 So in an unbalanced data situation, the Intercept is only approximately the grand mean. To see what you are requesting in the summary you can an offset from the mean and use the Intercept suppression syntax: model - lm(weight ~ Diet+0+offset(rep(mean(ChickWeight$weight), nrow(ChickWeight) )), ChickWeight) summary(model) Call: lm(formula = weight ~ Diet + 0 + offset(rep(mean(ChickWeight$weight), nrow(ChickWeight))), data = ChickWeight) Residuals: Min 1Q Median 3Q Max -103.95 -53.65 -13.64 40.38 230.05 Coefficients: Estimate Std. Error t value Pr(|t|) Diet1 -19.1729 4.6740 -4.102 4.69e-05 *** Diet2 0.7983 6.3286 0.126 0.899660 Diet3 21.1317 6.3286 3.339 0.000895 *** Diet4 13. 6.3820 2.107 0.035584 * --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 Residual standard error: 69.33 on 574 degrees of freedom Multiple R-squared: 0.7599,Adjusted R-squared: 0.7583 F-statistic: 454.3 on 4 and 574 DF, p-value: 2.2e-16 Notice this does estimate waht you requested, but I think it is more due to the use of an offset than to the choice of contrasts. with(ChickWeight, tapply(weight, Diet, function(categ) mean(categ)- mean(weight) ) ) 1 2 3 4 -19.1728846 0.7983276 21.1316609 13.4443728 I'm very worried this might be inferentially suspect, since the degrees of freedom and the anava F statistic are different than the usual methods. -- David. Thanks, Shaun On 26 June 2013 05:50, Adams, Jean jvad...@usgs.gov wrote: Shaun, See the help on contrasts ... ?contr.treatment Jean On Tue, Jun 25, 2013 at 7:07 PM, Shaun Jackman sjack...@gmail.com wrote: Hi, I've used `lm` to create a linear model of a continuous variable against a factor variable with four levels using an example R data set (see below). By default, it uses a treatment contrast matrix that compares each level of the factor variable with the first reference level (three comparisons in total). I'd like to compare each level with the global mean (four comparisons in total), and produce a table similar to `summary.lm`. How do I go about this? ```r model - lm(weight ~ Diet, ChickWeight) summary(model) ``` Thanks, Shaun __ 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. __ 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. David Winsemius Alameda, CA, USA __ 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.
Re: [R] Comparing each level of a factor to the global mean
Shaun, See the help on contrasts ... ?contr.treatment Jean On Tue, Jun 25, 2013 at 7:07 PM, Shaun Jackman sjack...@gmail.com wrote: Hi, I've used `lm` to create a linear model of a continuous variable against a factor variable with four levels using an example R data set (see below). By default, it uses a treatment contrast matrix that compares each level of the factor variable with the first reference level (three comparisons in total). I'd like to compare each level with the global mean (four comparisons in total), and produce a table similar to `summary.lm`. How do I go about this? ```r model - lm(weight ~ Diet, ChickWeight) summary(model) ``` Thanks, Shaun __ 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. [[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.
[R] Comparing each level of a factor to the global mean
Hi, I've used `lm` to create a linear model of a continuous variable against a factor variable with four levels using an example R data set (see below). By default, it uses a treatment contrast matrix that compares each level of the factor variable with the first reference level (three comparisons in total). I'd like to compare each level with the global mean (four comparisons in total), and produce a table similar to `summary.lm`. How do I go about this? ```r model - lm(weight ~ Diet, ChickWeight) summary(model) ``` Thanks, Shaun __ 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.
