I would like some advise on how I should analyse my time series data. I have hourly measurements of water temperature data for 5 months across 5 sites. I have summarized my data in following way 1.Site(5 sites) 2.Day (0-150) 2. Month (June-October, 5 levels) 3. Daily Mean Temperature(Response variable 1) 4. Daily Max Temperature (Response variable 2) 5. daily standard deviation,or some other measure of variation (Response variable 3) So I have 5 x 5 x 150 = 750 observations I want to test the following : - 1. Is my response variable significantly different between sites. 2.Is there a monthly interaction? For example in month 1 there all sites have similar response and in month 2 the one site will have significantly higher response than other sites. I am planning to do a time - series / or a mixed model analysis by specifying an temporal autocorrelation structure. For fixed effect I want the explanatory variables to be Option 1- month (as factor) , site(as factor) and interaction of these two. Option 2 - day (as a continous variable) and site (as factor) and intereaction of these two. Since this is a time series data I am expecting significant temporal autocorrelation. So when I do this analysis for mean and max temperature I should add a correlation structure. But I am not sure which variable should I use for correlation - month or Day ? Also I want to do an anova/ancova on standard deviation of daily temperature, so for this do I still need to add a correlation structure ? Or since it is a deviation, the values become independent ? Thank you
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Hi Julian, I would like your advise on how I should analyse my data using this analysis and if this analysis is suitable for my data. I have hourly measurements of water temperature data for 5 months across 5 sites. 24 x 30 x 5 x 5 = 18000 data points. I want to see if the water temperature is significantly different between sites at each month, and also if there is significant differences between sites overall i.e. site and site x month interaction. My data is is long format, with following col names 1.Site 2.Day number (0-150) 2. Month (June-October) 3. hours (0-24) 4. Temperature(Response variable) So I have been adding months and site in within subject factors. I am a bit confused about which factor to put in Subject ID, if it should be Day number or hours ? I am not interested to see hourly or daily variations. Also do you think I should use full-factorial repeated anova for my data or do you think I should rather do a mixed model by specifying a repeated structure (ex corAR1 etc) ? Thank you so much.
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