I used lme to fit a model which includes different variances for operators. My question is: What is the best way to report the operator standard deviations? Here are the details. My data contains an outcome, with predictors load (4 different loads) and operator (10 different operators). It is a very large unbalanced data set, with some operators only working on a single load while others operated on all 4 loads. I am interested in the load means, the operator means and the operator variances. The latter is my problem. I used the model lme(Outcome~Load,random=~1|Operator,weights = varIdent(form= ~ 1 | Operator),Data) I used intervals() to obtain estimates with 95% CIs of the effects of the loads and the operators. Because of identifiability, the model yields delta, the ratio of specific operator standard deviation to first operator standard deviation with their 95% CIs. The attached plot shows the deltas, with their confidence intervals. Is it correct to state that, because the some of the CIs do not overlap, the observer 4 is clearly less precise than some other observers? Thankyou in advance for advice. Regards Lize van der Merwe -------------- next part -------------- A non-text attachment was scrubbed... Name: Observers.pdf Type: application/pdf Size: 2121 bytes Desc: not available URL: <https://stat.ethz.ch/pipermail/r-sig-mixed-models/attachments/20180824/b848eb45/attachment.pdf>
how do I describe heteroscedacity
2 messages · Lize van der Merwe
1 day later
Dear mixed-models list Please help. I? used lme to fit a model which includes different variances for operators. My question is: ?????????????????????????????????????????????????????????????????????? What is the best way to report the operator standard deviations?? ? Here are the details. My data contains an outcome, with predictors load (4 different loads) and operator (10 different operators).? It is a very large unbalanced data set, with some operators only working on a single load while others operated on all 4 loads.? I am interested in the load means, the operator means and the operator variances.? The latter is my problem. I used the model ? lme(Outcome~Load,random=~1|Operator,weights = varIdent(form= ~ 1 | Operator),Data) I used intervals() to obtain estimates with 95% CIs of the effects of the loads and the operators.? ? Because of identifiability, the model yields delta, the ratio of specific operator standard deviation to first operator standard deviation with their 95% CIs.? The attached plot shows the deltas, with their confidence intervals.? Is it possible to estimate the standard deviations and their confidence intervals? Is it correct to state that, because the some of the CIs do not overlap, the observer 4 is clearly less precise than some other observers? Thankyou in advance for advice. Regards Lize van der Merwe -------------- next part -------------- A non-text attachment was scrubbed... Name: Observers.pdf Type: application/pdf Size: 2121 bytes Desc: not available URL: <https://stat.ethz.ch/pipermail/r-sig-mixed-models/attachments/20180825/5f0ed196/attachment.pdf>