How to get likelihood profile confidence intervals in LME?
As stated above you can get likelihood profile confidence intervals via confint (m); these may be computationally intensive. If you use confint (m, method=”Wald”) you’ll get the standard +/- 1.96SE confidence intervals. ( lme uses intervals (m) instead of confint () .)
How to get coefficients and their confidence intervals?
If you use confint (m, method=”Wald”) you’ll get the standard +/- 1.96SE confidence intervals. ( lme uses intervals (m) instead of confint () .) You can also get confidence intervals by parametric bootstrap ( method=”boot” ), which is considerably slower but more accurate in some circumstances.
Which is the confidence interval for random slope?
I am trying to figure out which confidence intervals are presented here. .sig01 appears to match the random intercept standard deviations, .sig03 for random slope time, .sigma for random residuals, and (Intercept) and time for the fixed effects. Is this correct? If so, what is .sig02 providing the confidence interval for? Thank you all in advance!
What are the confidence limits for lmer and glmer?
There are two new packages, lmerTest and lsmeans, that can calculate 95% confidence limits for lmer and glmer output. Maybe you can look into those?
How are confidence intervals for lmer objects through effects package?
– Cross Validated How trustworthy are the confidence intervals for lmer objects through effects package? Effects package provides a very fast and convenient way for plotting linear mixed effect model results obtained through lme4 package.
How is the effect function used to calculate confidence intervals?
The effect function calculates confidence intervals (CIs) very quickly, but how trustworthy are these confidence intervals?
What is the confidence interval for fish L?
The estimate for Fish L is on the top line, and has a very wide confidence interval. Fish K is on the third line, and has a very narrow confidence interval. This makes sense to me.
Is there way to make such a statement using lme4?
Fish D has really let himself go (1.11 oz) and is actually predicted to lose to Fish E and Fish F, both of whom he has been better than in the past. However, now I want to be able to say, “Fish E (weighing 0.91oz) will beat Fish D (weighing 1.11oz) with probability p.” Is there a way to make such a statement using lme4?