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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?
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 extract and plot confidence intervals in Excel?
So far I have tried confint, effects and lsmeans packages to extract the confidence intervals, being unsuccessful. Do you have any idea how this could be done? The plot shows the prediction interval when only varying poly (x, 6, raw = FALSE).
How to use lmer and confint in R?
I am using lmer () and confint () in R time: 4 time points, values 1,2,3,4. n: continuous dependent variable for neuroticism
How to use lmer function for cross validated?
Update the question so it’s on-topic for Cross Validated. Closed 3 years ago. I am trying to use lmer function from lme4 package to estimate differences between two response curves from a control and treatment responses over time, leaving Subjects as random effect. Here the data:
How to replicate lme4 time series confidence intervals?
If you want to replicate this using lme4 you can use the following (I use the sleepstudy data for reproducabilaty). Note that these datapoints are the same as that was trained on.
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 fixed and random effects estimated in GLMM?
Fixed effects are estimated using least squares (or, more generally, maximum likelihood) and random effects are estimated with shrinkage [“linear unbiased prediction” in the terminology of Robinson (1991)]. This definition is standard in the multilevel modeling literature [see, e.g., Snijders and Bosker (1999), Section 4.2] and in econometrics.
How to search for GLMM in StackOverflow?
Searching on StackOverflow with the [r] [mixed-models] tags, or on CrossValidated with the [mixed-model] tag may be helpful (these sites also have an [lme4] tag).