p-values from lme::anova VS fixed-effects of lme
Dear all, Firstly, my apology if this question is trivial. This question is related to this post at http://stats.stackexchange.com/questions/7185/what-is-the-difference-between-using-aov-and-lme-in-analyzing-a-longitudinal . My I ask a question is: If I rerun these codes (lme) #### LME ###### res <- lme(distance ~ age*Sex, random = ~ 1 | Subject, data = Orthodont) summary(res) ################ I would obtain this ##################################################### Fixed effects: distance ~ age * Sex Value Std.Error DF t-value p-value (Intercept) 16.340625 0.9813122 79 16.651810 0.0000 age 0.784375 0.0775011 79 10.120823 0.0000 SexFemale 1.032102 1.5374208 25 0.671321 0.5082 age:SexFemale -0.304830 0.1214209 79 -2.510520 0.0141 ######################################################## Next, if I run 'anova(res)', I would obtain this ###ANOVA#### numDF denDF F-value p-value (Intercept) 1 79 4123.156 <.0001 age 1 79 122.450 <.0001 Sex 1 25 9.292 0.0054 age:Sex 1 79 6.303 0.0141 ############### I do not understand why the p-values for age and age:Sex (from anova) are similar with (lme::anova) BUT for sex: it is different (anova, p-val = 0.0054 vs lme::anova, p-val = 0.508). Your kind attention is very much appreciated. Thanks and best wishes, Kamarul
Dr. Kamarul Imran Musa (MD MCommunityMed) Associate Professor (Epidemiology and Biostatistics) & Public Health Physician, Address: Dept of Community Medicine, School of Medical Sciences, Universiti Sains Malaysia, 16150 Kbg Kerian Kelantan MALAYSIA ResearcherID: http://www.researcherid.com/rid/N-3198-2015 Google-scholar: 'Kamarul Imran Musa' at https://goo.gl/D3o3y6 ORCID ID: orcid.org/0000-0002-3708-0628 ScopusID: 18634847200 Personal web: www.myanalytics.com.my Alt emails : drkamarul at usm.my , k.musa at lancaster.ac.uk [[alternative HTML version deleted]]