![]() yields different results - neither the same as the results from SPSS The syntax below gives me the same unadjusted results as someone (who is now AWOL) got in SPSS:Īnova y trt/pid|trt week trt#week,rep(week)Īnova y c.age trt/pid|trt week trt#week,rep(week)Īnova y trt/pid|trt week trt#week c.age,rep(week) I would like to know the effect of Vit D supplementation vs placebo (trt) on outcome y at 52 weeks compared to baseline (week = 0 or 52) I have been able to control for age using c.age, but the results vary depending on where I put it in the model. I have tried a few codes, but as I'm a bit of a Stata novice, I'm not exactly sure what the syntax I'm using means. I want to control for one continuous (age) and one categorical variable (sex) at baseline. I have a question despite all the help that has been provided here - I am trying to run a 2 x 2 (trt x week) RM ANCOVA. Any insight would be greatly appreciated!Īnova y c.x a / individual#a c.x b a#b, repeated(b) bse(individual#a) My overall output looks correct for my other variables in the model, except for the covariate, which drastically differs from what I get using JMP and R. ) but the information for adding in a covariate or running repeated measures ANCOVA has been difficult to find. I've found an abundance of information regarding repeated measures anova using Stata online (e.g. While I followed Joseph Coveney's syntax closely, I've noticed that the output for my covariate does not match what I have found when I run the same model in JMP and R. My data includes a sample of 200 participants receiving 2 types of treatment, performance prior to treatment (covariate that is used as a baseline/control), and performance at 5 different time points following treatment. Hello, I wanted to follow up on this thread as I fit a repeated measures ANCOVA to my model. But that residual is pretty huge, isn't it? Do I need to consider refining the model? Is this even possible? It doesn't seem so from the menu dialogue box.Ĭode: Number of obs = 382 R-squared = 0.7133 But since pH changes, and can influence TR, ideally I would use it as a repeated measures covariate. Or I could use it as a continuous variable. I can use the former if I block or bin pH0 and use that as a independent ordinal variable in the model. I thought that repeated-measures ANOVA or ANCOVA might help here. So, I have an ordinal independent variable, CONC, a nominally ordinal independent variable, pH0 (which is in effect more continuous than ordinal), and repeated measures of interest (TR0, TR1). pH0 was fixed as much as possible, but varied within each nominal group, and changed slightly over the incubation period (it's a bicarbonate-buffered medium). TR and pH were measured at the start (TR0, pH0) and end (TR1, pH1) of culture. We hypothesise that TR is affected by both drug and pH, so tissues were incubated for one hour in varying concentrations of drug and different pH. I have a study in which we evaluated the effects of a drug and pH of the culture medium upon the twitch rate (TR) of tissue in vitro. ![]()
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