# multiple GLMs with lmList in lme4

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## multiple GLMs with lmList in lme4

 I'd like to fit a GLM to each of a number of subsets of some data. The `family' argument to `lmList' (in lme4) has given me cause for optimism, but so far I've only been able to achieve linear model fits. For example > df <- data.frame(gp = gp.temp <- factor(rep(1:3, each = 100)), x = x.temp <- rnorm(300), y = rpois(300, exp((-1:1)[gp.temp] + x.temp))) Then a call to `glm' on the group 1 subset gives > glm(y ~ x, family = poisson, data = df, subset = gp == 1) Call:  glm(formula = y ~ x, family = poisson, data = df, subset = gp == 1) Coefficients: (Intercept)            x       -1.0143       0.9726   Degrees of Freedom: 99 Total (i.e. Null);  98 Residual Null Deviance:      138.5 Residual Deviance: 82.76        AIC: 178.5 (the right answer) but `lmList' gives > show(lmList(y ~ x | gp, family = poisson, data = df)) Call: lmList(formula = y ~ x | gp, data = df, family = poisson) Coefficients:   (Intercept)         x 1   0.5560377 0.6362124 2   1.8431794 1.8541193 3   4.5773106 4.7871929 Degrees of freedom: 300 total; 294 residual Residual standard error: 2.655714 which come from linear model fits, e.g. > lm(y ~ x, data = df, subset = gp == 1) Call: lm(formula = y ~ x, data = df, subset = gp == 1) Coefficients: (Intercept)            x        0.5560       0.6362 Any suggestions as to why lmList matches the linear fits rather than the GLM fits would be greatly appreciated. I'm using R2.2.1 with lme version 0.98-1 in Windows XP. Daniel Farewell Cardiff University ______________________________________________ [hidden email] mailing list https://stat.ethz.ch/mailman/listinfo/r-helpPLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
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## Re: multiple GLMs with lmList in lme4

 On Tue, 17 Jan 2006, Daniel Farewell wrote: > I'd like to fit a GLM to each of a number of subsets of some data. The > `family' argument to `lmList' (in lme4) has given me cause for optimism, > but so far I've only been able to achieve linear model fits. For example > >> df <- data.frame(gp = gp.temp <- factor(rep(1:3, each = 100)), > x = x.temp <- rnorm(300), > y = rpois(300, exp((-1:1)[gp.temp] + x.temp))) Unless you are particularly attached to lmList() you might try by(): by(df,df\$gp,function(subset) glm(y~x,family=poisson,data=subset))   -thomas > > Then a call to `glm' on the group 1 subset gives > >> glm(y ~ x, family = poisson, data = df, subset = gp == 1) > > Call:  glm(formula = y ~ x, family = poisson, data = df, subset = gp == 1) > > Coefficients: > (Intercept)            x >    -1.0143       0.9726 > > Degrees of Freedom: 99 Total (i.e. Null);  98 Residual > Null Deviance:      138.5 > Residual Deviance: 82.76        AIC: 178.5 > > (the right answer) but `lmList' gives > >> show(lmList(y ~ x | gp, family = poisson, data = df)) > Call: lmList(formula = y ~ x | gp, data = df, family = poisson) > Coefficients: >  (Intercept)         x > 1   0.5560377 0.6362124 > 2   1.8431794 1.8541193 > 3   4.5773106 4.7871929 > > Degrees of freedom: 300 total; 294 residual > Residual standard error: 2.655714 > > which come from linear model fits, e.g. > >> lm(y ~ x, data = df, subset = gp == 1) > > Call: > lm(formula = y ~ x, data = df, subset = gp == 1) > > Coefficients: > (Intercept)            x >     0.5560       0.6362 > > Any suggestions as to why lmList matches the linear fits rather than the GLM fits would be greatly appreciated. I'm using R2.2.1 with lme version 0.98-1 in Windows XP. > > Daniel Farewell > Cardiff University > > ______________________________________________ > [hidden email] mailing list > https://stat.ethz.ch/mailman/listinfo/r-help> PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html> Thomas Lumley Assoc. Professor, Biostatistics [hidden email] University of Washington, Seattle ______________________________________________ [hidden email] mailing list https://stat.ethz.ch/mailman/listinfo/r-helpPLEASE do read the posting guide! http://www.R-project.org/posting-guide.html