 <!--  /* Style Definitions */  p.MsoNormal, li.MsoNormal, div.MsoNormal 	{mso-style-parent:""; 	margin:0cm; 	margin-bottom:.0001pt; 	mso-pagination:widow-orphan; 	font-size:12.0pt; 	font-family:"Times New Roman"; 	mso-fareast-font-family:"Times New Roman";} @page Section1 	{size:595.3pt 841.9pt; 	margin:70.85pt 70.85pt 2.0cm 70.85pt; 	mso-header-margin:35.4pt; 	mso-footer-margin:35.4pt; 	mso-paper-source:0;} div.Section1 	{page:Section1;} -->   Hello!  I have to analyze a repeated measures ANOVA, and I know, that I have to do this using the lmer-function- I just dont know, how to formulate my model, I red so many different advices.  I measured fluorescence parameters on 4 different species under 2 different treatments (5 real replicates) on 6 different days. I made normal ANOVAs for the single days, just to know, if there are treatment effects within the single species. But now I want to know  the development of one treatment over time (I´m not so interested in the development of the control-treatment over time). So I have to make clear, that the data from the single days are pseudo-replicates and not independent, because they are taken from the same plants. I created subset for the single species and the treatment I am interested in (is this valid??) and took only two days to compare at a time (because I think theres no post-hoc test to show, which days differ?), so the only factors are doy (day of the year) and repetition (replicates 1-5). That’s how I formulated the model (Yieldmedian is the response variable)     fm<-lmer(Yieldmedian~doy+(doy|repetition),data=…)    Is this correct? I guess not, because when I did normal ANOVA     fm<-lm(Yieldmedian~doy+repetition,data=…)  anova(h)     the results were the same. Why?   Or do I have to do a bounded t-test? How?     thanks for you advice!
j.





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