[R] Factor moderators in metafor
I'm puzzled by the behaviour of factors in rma models, see example and comments below. I'm sure there's a simple explanation but can't see it... Thanks for any input John Hodgson - code/selected output - library(metafor) ##Set up data (from Lenters et al A Meta-analysis of Asbestos and Lung Cancer... ##Environmental Health Perspectives • volume 119 | number 11 | November 2011) KL = c(0.02905, 0.06929, -0.1523, 1.6441, 0.1215, 0.3975, 1.0566, 0.1257, 0.2277, 0.06791, 0.08164, 0.2526, 0.07577, 0.03266, 0.1141, 0.1836, 1.8276, 0.4149, 15.4974) SE = c(0.006633, 0.09335, 0.08909, 0.4297, 0.07858, 0.1753, 0.3679, 0.1837, 0.2172, 0.2775, 0.4201, 0.1976, 0.7688, 0.06507, 0.06239, 0.09061, 0.9509, 0.2181, 7.331) VL = SE*SE amph = c(0, 0, 0, 0, 0, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0) mix =c(0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1) ftype = c(0, 0, 0, 0, 0, 1, 1, 1, 1, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2) factor(amph) factor(ftype) factor(mix) ## Fit ftype... rma(KL,VL,mods=ftype) Mixed-Effects Model (k = 19; tau^2 estimator: REML) tau^2 (estimate of residual amount of heterogeneity): 0.0111 (SE = 0.0095) tau (sqrt of the estimate of residual heterogeneity): 0.1054 Test for Residual Heterogeneity: QE(df = 17) = 43.0937, p-val = 0.0005 Test of Moderators (coefficient(s) 2): QM(df = 1) = 1.1069, p-val = 0.2928 Model Results: estimate sezvalpvalci.lb ci.ub intrcpt0.0811 0.0606 1.3380 0.1809 -0.0377 0.2000 mods 0.0473 0.0449 1.0521 0.2928 -0.0408 0.1353 Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 ## why only one df for the 2-level factor? ## in other words, why isn't the above model the same as the following... rma(KL,VL,mods=cbind(amph,mix)) Mixed-Effects Model (k = 19; tau^2 estimator: REML) tau^2 (estimate of residual amount of heterogeneity): 0.0030 (SE = 0.0046) tau (sqrt of the estimate of residual heterogeneity): 0.0549 Test for Residual Heterogeneity: QE(df = 16) = 37.5762, p-val = 0.0017 Test of Moderators (coefficient(s) 2,3): QM(df = 2) = 6.9220, p-val = 0.0314 Model Results: estimate sezvalpvalci.lb ci.ub intrcpt0.0380 0.0402 0.9448 0.3447 -0.0408 0.1169 amph 0.2879 0.1163 2.4754 0.0133 0.0599 0.5158 * mix0.0888 0.0625 1.4199 0.1556 -0.0338 0.2114 --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 -- View this message in context: http://r.789695.n4.nabble.com/Factor-moderators-in-metafor-tp4639745.html Sent from the R help mailing list archive at Nabble.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.
Re: [R] Factor moderators in metafor
There is a simple explanation: 1) The command: factor(ftype) does not actually turn 'ftype' permanently into a factor, since you are not re-assigning it back to the object 'ftype'. You have to use: ftype - factor(ftype) 2) If you want to use the formula interface for specifying moderators, you have to use mods = ~ formula, so in other words: rma(KL, VL, mods = ~ ftype) after you have made 'ftype' a factor (see 1). Or you can simply use: rma(KL, VL, mods = ~ factor(ftype)) which does the conversion of 'ftype' into a factor within the model formula. Best, Wolfgang -- Wolfgang Viechtbauer, Ph.D., Statistician Department of Psychiatry and Psychology School for Mental Health and Neuroscience Faculty of Health, Medicine, and Life Sciences Maastricht University, P.O. Box 616 (VIJV1) 6200 MD Maastricht, The Netherlands +31 (43) 388-4170 | http://www.wvbauer.com -Original Message- From: r-help-boun...@r-project.org [mailto:r-help-boun...@r-project.org] On Behalf Of John Hodgson Sent: Thursday, August 09, 2012 12:56 To: r-help@r-project.org Subject: [R] Factor moderators in metafor I'm puzzled by the behaviour of factors in rma models, see example and comments below. I'm sure there's a simple explanation but can't see it... Thanks for any input John Hodgson - code/selected output --- -- library(metafor) ##Set up data (from Lenters et al A Meta-analysis of Asbestos and Lung Cancer... ##Environmental Health Perspectives • volume 119 | number 11 | November 2011) KL = c(0.02905, 0.06929, -0.1523, 1.6441, 0.1215, 0.3975, 1.0566, 0.1257, 0.2277, 0.06791, 0.08164, 0.2526, 0.07577, 0.03266, 0.1141, 0.1836, 1.8276, 0.4149, 15.4974) SE = c(0.006633, 0.09335, 0.08909, 0.4297, 0.07858, 0.1753, 0.3679, 0.1837, 0.2172, 0.2775, 0.4201, 0.1976, 0.7688, 0.06507, 0.06239, 0.09061, 0.9509, 0.2181, 7.331) VL = SE*SE amph = c(0, 0, 0, 0, 0, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0) mix =c(0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1) ftype = c(0, 0, 0, 0, 0, 1, 1, 1, 1, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2) factor(amph) factor(ftype) factor(mix) ## Fit ftype... rma(KL,VL,mods=ftype) Mixed-Effects Model (k = 19; tau^2 estimator: REML) tau^2 (estimate of residual amount of heterogeneity): 0.0111 (SE = 0.0095) tau (sqrt of the estimate of residual heterogeneity): 0.1054 Test for Residual Heterogeneity: QE(df = 17) = 43.0937, p-val = 0.0005 Test of Moderators (coefficient(s) 2): QM(df = 1) = 1.1069, p-val = 0.2928 Model Results: estimate sezvalpvalci.lb ci.ub intrcpt0.0811 0.0606 1.3380 0.1809 -0.0377 0.2000 mods 0.0473 0.0449 1.0521 0.2928 -0.0408 0.1353 Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 ## why only one df for the 2-level factor? ## in other words, why isn't the above model the same as the following... rma(KL,VL,mods=cbind(amph,mix)) Mixed-Effects Model (k = 19; tau^2 estimator: REML) tau^2 (estimate of residual amount of heterogeneity): 0.0030 (SE = 0.0046) tau (sqrt of the estimate of residual heterogeneity): 0.0549 Test for Residual Heterogeneity: QE(df = 16) = 37.5762, p-val = 0.0017 Test of Moderators (coefficient(s) 2,3): QM(df = 2) = 6.9220, p-val = 0.0314 Model Results: estimate sezvalpvalci.lb ci.ub intrcpt0.0380 0.0402 0.9448 0.3447 -0.0408 0.1169 amph 0.2879 0.1163 2.4754 0.0133 0.0599 0.5158 * mix0.0888 0.0625 1.4199 0.1556 -0.0338 0.2114 --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 __ 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] Factor moderators in metafor
Thanks, I suspected it would be something simple. Best wishes John On 09/08/2012 14:42, Viechtbauer Wolfgang (STAT)-2 [via R] wrote: There is a simple explanation: 1) The command: factor(ftype) does not actually turn 'ftype' permanently into a factor, since you are not re-assigning it back to the object 'ftype'. You have to use: ftype - factor(ftype) 2) If you want to use the formula interface for specifying moderators, you have to use mods = ~ formula, so in other words: rma(KL, VL, mods = ~ ftype) after you have made 'ftype' a factor (see 1). Or you can simply use: rma(KL, VL, mods = ~ factor(ftype)) which does the conversion of 'ftype' into a factor within the model formula. Best, Wolfgang -- Wolfgang Viechtbauer, Ph.D., Statistician Department of Psychiatry and Psychology School for Mental Health and Neuroscience Faculty of Health, Medicine, and Life Sciences Maastricht University, P.O. Box 616 (VIJV1) 6200 MD Maastricht, The Netherlands +31 (43) 388-4170 | http://www.wvbauer.com -Original Message- From: [hidden email] /user/SendEmail.jtp?type=nodenode=4639763i=0 [mailto:[hidden email] /user/SendEmail.jtp?type=nodenode=4639763i=1] On Behalf Of John Hodgson Sent: Thursday, August 09, 2012 12:56 To: [hidden email] /user/SendEmail.jtp?type=nodenode=4639763i=2 Subject: [R] Factor moderators in metafor I'm puzzled by the behaviour of factors in rma models, see example and comments below. I'm sure there's a simple explanation but can't see it... Thanks for any input John Hodgson - code/selected output --- -- library(metafor) ##Set up data (from Lenters et al A Meta-analysis of Asbestos and Lung Cancer... ##Environmental Health Perspectives ⢠volume 119 | number 11 | November 2011) KL = c(0.02905, 0.06929, -0.1523, 1.6441, 0.1215, 0.3975, 1.0566, 0.1257, 0.2277, 0.06791, 0.08164, 0.2526, 0.07577, 0.03266, 0.1141, 0.1836, 1.8276, 0.4149, 15.4974) SE = c(0.006633, 0.09335, 0.08909, 0.4297, 0.07858, 0.1753, 0.3679, 0.1837, 0.2172, 0.2775, 0.4201, 0.1976, 0.7688, 0.06507, 0.06239, 0.09061, 0.9509, 0.2181, 7.331) VL = SE*SE amph = c(0, 0, 0, 0, 0, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0) mix =c(0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1) ftype = c(0, 0, 0, 0, 0, 1, 1, 1, 1, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2) factor(amph) factor(ftype) factor(mix) ## Fit ftype... rma(KL,VL,mods=ftype) Mixed-Effects Model (k = 19; tau^2 estimator: REML) tau^2 (estimate of residual amount of heterogeneity): 0.0111 (SE = 0.0095) tau (sqrt of the estimate of residual heterogeneity): 0.1054 Test for Residual Heterogeneity: QE(df = 17) = 43.0937, p-val = 0.0005 Test of Moderators (coefficient(s) 2): QM(df = 1) = 1.1069, p-val = 0.2928 Model Results: estimate sezvalpvalci.lb ci.ub intrcpt0.0811 0.0606 1.3380 0.1809 -0.0377 0.2000 mods 0.0473 0.0449 1.0521 0.2928 -0.0408 0.1353 Signif. codes: 0 â***â 0.001 â**â 0.01 â*â 0.05 â.â 0.1 â â 1 ## why only one df for the 2-level factor? ## in other words, why isn't the above model the same as the following... rma(KL,VL,mods=cbind(amph,mix)) Mixed-Effects Model (k = 19; tau^2 estimator: REML) tau^2 (estimate of residual amount of heterogeneity): 0.0030 (SE = 0.0046) tau (sqrt of the estimate of residual heterogeneity): 0.0549 Test for Residual Heterogeneity: QE(df = 16) = 37.5762, p-val = 0.0017 Test of Moderators (coefficient(s) 2,3): QM(df = 2) = 6.9220, p-val = 0.0314 Model Results: estimate sezvalpvalci.lb ci.ub intrcpt0.0380 0.0402 0.9448 0.3447 -0.0408 0.1169 amph 0.2879 0.1163 2.4754 0.0133 0.0599 0.5158 * mix0.0888 0.0625 1.4199 0.1556 -0.0338 0.2114 --- Signif. codes: 0 â***â 0.001 â**â 0.01 â*â 0.05 â.â 0.1 â â 1 __ [hidden email] /user/SendEmail.jtp?type=nodenode=4639763i=3 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. If you reply to this email, your message will be added to the discussion below: http://r.789695.n4.nabble.com/Factor-moderators-in-metafor-tp4639745p4639763.html To unsubscribe from Factor moderators in metafor, click here http://r.789695.n4.nabble.com/template/NamlServlet.jtp?macro=unsubscribe_by_codenode=4639745code=am9obkBmb3JtYnkucGx1cy5jb218NDYzOTc0NXwtMTEzNDA5Nzc0Mw==. NAML http://r.789695.n4.nabble.com/template/NamlServlet.jtp?macro=macro_viewerid
