Re: [R] [R-sig-ME] lme function to obtain pvalue for fixed effect
Because they test different hypothesis. ir. Thierry Onkelinx Instituut voor natuur- en bosonderzoek / Research Institute for Nature and Forest team Biometrie Kwaliteitszorg / team Biometrics Quality Assurance Kliniekstraat 25 1070 Anderlecht Belgium To call in the statistician after the experiment is done may be no more than asking him to perform a post-mortem examination: he may be able to say what the experiment died of. ~ Sir Ronald Aylmer Fisher The plural of anecdote is not data. ~ Roger Brinner The combination of some data and an aching desire for an answer does not ensure that a reasonable answer can be extracted from a given body of data. ~ John Tukey 2015-05-26 21:46 GMT+02:00 li li hannah@gmail.com: Thanks so much for replying. Yes LimerTest package could be used to get pvalues when using lmer function. But still the summary and anova function give different pvalues. Hanna 2015-05-26 15:19 GMT-04:00, byron vinueza byronvin...@hotmail.com: You can use the lmerTest package . Enviado desde mi iPhone El 26/5/2015, a las 13:18, li li hannah@gmail.com escribió: Hi all, I am using the lme function to run a random coefficient model. Please see output (mod1) as below. I need to obtain the pvalue for the fixed effect. As you can see, the pvalues given using the summary function is different from the resutls given in anova function. Why should they be different and which one is the correct one to use? Thanks! Hanna summary(mod1) Linear mixed-effects model fit by REML Data: minus20C1 AIC BIC logLik -82.60042 -70.15763 49.30021 Random effects: Formula: ~1 + months | lot Structure: General positive-definite, Log-Cholesky parametrization StdDev Corr (Intercept) 8.907584e-03 (Intr) months 6.039781e-05 -0.096 Residual4.471243e-02 Fixed effects: ti ~ type * months Value Std.Error DF t-value p-value (Intercept) 0.25831245 0.016891587 31 15.292373 0. type 0.13502089 0.026676101 4 5.061493 0.0072 months 0.00804790 0.001218941 31 6.602368 0. type:months -0.00693679 0.002981859 31 -2.326329 0.0267 Correlation: (Intr) typ months type-0.633 months -0.785 0.497 type:months 0.321 -0.762 -0.409 Standardized Within-Group Residuals: MinQ1 MedQ3 Max -2.162856e+00 -1.962972e-01 -2.771184e-05 3.749035e-01 2.088392e+00 Number of Observations: 39 Number of Groups: 6 anova(mod1) numDF denDF F-value p-value (Intercept) 131 2084.0265 .0001 type1 4 10.8957 0.0299 months 131 38.3462 .0001 type:months 1315.4118 0.0267 ___ r-sig-mixed-mod...@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-sig-mixed-models ___ r-sig-mixed-mod...@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-sig-mixed-models [[alternative HTML version deleted]] __ R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see 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] [R-sig-ME] lme function to obtain pvalue for fixed effect
You can use the lmerTest package . Enviado desde mi iPhone El 26/5/2015, a las 13:18, li li hannah@gmail.com escribió: Hi all, I am using the lme function to run a random coefficient model. Please see output (mod1) as below. I need to obtain the pvalue for the fixed effect. As you can see, the pvalues given using the summary function is different from the resutls given in anova function. Why should they be different and which one is the correct one to use? Thanks! Hanna summary(mod1) Linear mixed-effects model fit by REML Data: minus20C1 AIC BIC logLik -82.60042 -70.15763 49.30021 Random effects: Formula: ~1 + months | lot Structure: General positive-definite, Log-Cholesky parametrization StdDev Corr (Intercept) 8.907584e-03 (Intr) months 6.039781e-05 -0.096 Residual4.471243e-02 Fixed effects: ti ~ type * months Value Std.Error DF t-value p-value (Intercept) 0.25831245 0.016891587 31 15.292373 0. type 0.13502089 0.026676101 4 5.061493 0.0072 months 0.00804790 0.001218941 31 6.602368 0. type:months -0.00693679 0.002981859 31 -2.326329 0.0267 Correlation: (Intr) typ months type-0.633 months -0.785 0.497 type:months 0.321 -0.762 -0.409 Standardized Within-Group Residuals: MinQ1 MedQ3 Max -2.162856e+00 -1.962972e-01 -2.771184e-05 3.749035e-01 2.088392e+00 Number of Observations: 39 Number of Groups: 6 anova(mod1) numDF denDF F-value p-value (Intercept) 131 2084.0265 .0001 type1 4 10.8957 0.0299 months 131 38.3462 .0001 type:months 1315.4118 0.0267 ___ r-sig-mixed-mod...@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-sig-mixed-models __ R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see 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] [R-sig-ME] lme function to obtain pvalue for fixed effect
Thanks so much for replying. Yes LimerTest package could be used to get pvalues when using lmer function. But still the summary and anova function give different pvalues. Hanna 2015-05-26 15:19 GMT-04:00, byron vinueza byronvin...@hotmail.com: You can use the lmerTest package . Enviado desde mi iPhone El 26/5/2015, a las 13:18, li li hannah@gmail.com escribió: Hi all, I am using the lme function to run a random coefficient model. Please see output (mod1) as below. I need to obtain the pvalue for the fixed effect. As you can see, the pvalues given using the summary function is different from the resutls given in anova function. Why should they be different and which one is the correct one to use? Thanks! Hanna summary(mod1) Linear mixed-effects model fit by REML Data: minus20C1 AIC BIC logLik -82.60042 -70.15763 49.30021 Random effects: Formula: ~1 + months | lot Structure: General positive-definite, Log-Cholesky parametrization StdDev Corr (Intercept) 8.907584e-03 (Intr) months 6.039781e-05 -0.096 Residual4.471243e-02 Fixed effects: ti ~ type * months Value Std.Error DF t-value p-value (Intercept) 0.25831245 0.016891587 31 15.292373 0. type 0.13502089 0.026676101 4 5.061493 0.0072 months 0.00804790 0.001218941 31 6.602368 0. type:months -0.00693679 0.002981859 31 -2.326329 0.0267 Correlation: (Intr) typ months type-0.633 months -0.785 0.497 type:months 0.321 -0.762 -0.409 Standardized Within-Group Residuals: MinQ1 MedQ3 Max -2.162856e+00 -1.962972e-01 -2.771184e-05 3.749035e-01 2.088392e+00 Number of Observations: 39 Number of Groups: 6 anova(mod1) numDF denDF F-value p-value (Intercept) 131 2084.0265 .0001 type1 4 10.8957 0.0299 months 131 38.3462 .0001 type:months 1315.4118 0.0267 ___ r-sig-mixed-mod...@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-sig-mixed-models __ R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see 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.
