lme for data that is not normally distributed
Thank very much?for?your helpful advice. I ran?the model and tested the residuals. They are not normally distributed, and I am still stuck with how I proceed.?I tried to copy the output on the email, but I get an error message that the message format cannot sent. Regards, Moses??
On Wednesday, 3 August 2016, 12:15, Highland Statistics Ltd <highstat at highstat.com> wrote:
Date: Wed, 3 Aug 2016 09:40:20 +0000 (UTC) From: moses selebatso <selebatsom at yahoo.co.uk> To: R-sig-mixed-models <r-sig-mixed-models at r-project.org> Subject: [R-sig-ME] lme for data that is not normally distributed Message-ID: ??? <127496753.15122202.1470217220406.JavaMail.yahoo at mail.yahoo.com> Content-Type: text/plain; charset="UTF-8" ?Hello I have some data that I would to analyse with mixed models (lme). As a standard procedure I tested for the normality of the data and it is not normal. Any ideas of how deals with this kind of data? I have a sample below and the model that I was hoping to use (if?the data?was normal) m <- lme(Distance~Time,random=~1|ID,data=data).
Checking normality of the response variable before doing the analysis is a misconception. Why should it be normally distributed? Fit your model and check your residuals for normality. Alain
? ? | ? | ID | ? | Time | ? | Distance | ? ? | ? | 10187A | ? | Pre_dry | ? | 4.31287 | ? ? | ? | 10187A | ? | Pre_dry | ? | 6.867578 | ? ? | ? | 10187A | ? | Pre_dry | ? | 4.640427 | ? ? | ? | 10187A | ? | Post_dry | ? | 4.497807 | ? ? | ? | 10187A | ? | Post_dry | ? | 9.726069 | ? ? | ? | 10187A | ? | Post_dry | ? | 5.150089 | ? Regards, Moses SELEBATSO? ??? [[alternative HTML version deleted]] ------------------------------ Subject: Digest Footer
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Dr. Alain F. Zuur First author of: 1. Beginner's Guide to GAMM with R (2014). 2. Beginner's Guide to GLM and GLMM with R (2013). 3. Beginner's Guide to GAM with R (2012). 4. Zero Inflated Models and GLMM with R (2012). 5. A Beginner's Guide to R (2009). 6. Mixed effects models and extensions in ecology with R (2009). 7. Analysing Ecological Data (2007). Highland Statistics Ltd. 9 St Clair Wynd UK - AB41 6DZ Newburgh Tel:? 0044 1358 788177 Email: highstat at highstat.com URL:? www.highstat.com _______________________________________________ R-sig-mixed-models at r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-sig-mixed-models [[alternative HTML version deleted]]