Questions tagged [reml]

Restricted maximum likelihood (reml) is a variant of maximum likelihood when estimation is based on some transformations of the data, typically to residuals.

21 questions with no upvoted or accepted answers
Filter by
Sorted by
Tagged with
3
votes
0answers
49 views

Are REML estimators of variance-covariance parameters consistent?

I am trying to locate some reference papers about consistency of REML estimators in linear mixed effects models. My understanding is that in linear model scenario, REML will produce the exact same ...
2
votes
0answers
77 views

REML in non-mixed models

I want to know if the concept of Restricted Maximum Likelihood (REML) applies to non-mixed models. For example, suppose we want to perform a test equivalent of the one-sample t-test, it may be ...
2
votes
0answers
97 views

Model selection with different fixed effects and different corARMA structures

I analyzed the effect of temperature (4 different areas) on laying date: LDT ~ Aa3+Bb+Cc+Dd. Because of autocorrelation in residuals I used ...
2
votes
0answers
67 views

REML estimation - matrix algebra internals

In the context of REML estimation there is the result (ignoring some constants) that (my interest is in the matrix algebra so some notation is suppressed): $l(\mathbf V_0)=\log |\mathbf V_0| + \text{...
2
votes
0answers
249 views

assumptions of REML

In Patterson and Thompson 1971, $L$ is the log-likelihood of $y$ $$ L = const - \frac{1}{2}log |H| - \frac{1}{2}n log (\sigma^2) - \frac{1}{2\sigma^2} (y - X\alpha)'H^{-1}(y-Xa) $$ They consider the ...
1
vote
0answers
30 views

What does it mean to have a model fit via GLS with REML? Aren't GLS and REML two different methods of estimation?

As in the title. I am confused. We often read that a regression model was fit using the OLS, GLS, TLS or ML. But recently I found a text about the analysis of repeated data, where it was modelled ...
1
vote
0answers
9 views

Score test using restricted mle

I am doing a study on Rao score test and still confused about the score vector. How am I supposed to calculate the score vector? Can I just use (ˆθn - θn) for the score vector? As I understood that ...
1
vote
0answers
54 views

Why do I not get confidence intervals for interactions using confint with glmmTMB (nbinom2) and REML=TRUE

I run a model where I test the effects of different parameters on the number of individuals (no_ind) in a field experiment. I would like to report the confidence intervals and use confint() which ...
1
vote
0answers
22 views

Hartung-Knapp-Sidik-Jonkman variance correction in meta-analysis

I am doing a meta-analysis of continuous data (SMD), number of studies (k) around 75, heterogeneity high (Tau-squared around 0.15, I-sqr over 75%). Our interest is in fact in a key subgroup analysis (...
1
vote
0answers
164 views

Restricted Maximum Likelihood Estimation for Linear Mixed Model

The maximum likelihood estimation procedure for linear mixed model is described in this link. It seems to me that something is wrong there. In their Restricted Maximum Likelihood section the first ...
1
vote
0answers
204 views

Mixed Linear Model - REML approach AI or FS algorithm

I am trying to see if there is a situation where Fisher scoring algorithm would be better than Average Information algorithm. I know that Average information algorithm is more efficient for large data ...
0
votes
0answers
12 views

Regression model selection and specification for unbalanced repeated measures data

My hypothesis is that person's blood oxygen level is affected by their age, gender, and drugs they have taken in the previous 24 hours. I would like to confirm and quantify effects associated with ...
0
votes
0answers
18 views

Random-intercept model with three levels: heteroschedasticity of level-1 and non-normality of level-2 residuals?

I am working on a random-intercept model with three levels and I have questions regarding the distribution of the residuals and its effect on coefficients and confidence intervals. But first let me ...
0
votes
0answers
112 views

Model smoothness selection for GAMs: GCV vs. REML vs. ML?

I am studying patterns of bird abundances with certain habitat variables and how they vary over time. I am interested in using GAMs with smooth terms for some of the variables. I am, however, confused ...
0
votes
0answers
30 views

Are the Generalized Least Square (GLS) and Maximum Likelihood (ML) two different ways of estimation?

I was taught, that OLS and ML are two different ways of estimation. ML gives OLS estimates under met assuptions, but it doesn't change the fact the two approaches differ. If so, how is that possible ...
0
votes
1answer
44 views

Show why the estimate of variance component using REML is unbiased

I'm trying to use a very simple example to illustrate how REML makes the estimate of variance component unbiased: Consider $X_1,\dots,X_n\overset{i.i.d.}{\sim}\mathcal{N}(\mu,\sigma^2)$, we denote one ...
0
votes
1answer
90 views

tau2 estimation using reml in SAS

I would like to obtain tau2 estimation using REML by making use of PROC MIXED procedure in SAS to compare the estimation result obtained from rma function in R. I have used the following SAS code; ...
0
votes
0answers
186 views

Using ML or REML when comparing factor levels with Wald test?

I have finished my model reduction of a linear mixed model (and have used ML for this) and have found which factors that are significant in my final model. I am aware of that using ML is necessary ...
0
votes
0answers
801 views

“Time” as continuous, ordinal, or nominal in this REML design?

I've assayed two treatment groups at three time points. The time points are "days post inoculation" (specifically, 0, 20 and 40 days), so the interval between the measure is meaningful. I've ...
0
votes
1answer
696 views

Big Misconception in the use of REML to estimate Variance Components?

I often hear from my classmates, and even in resources on the internet such as in the abstract to this paper, what I now believe to be a misconception regarding the motivation of using REML (...
0
votes
0answers
137 views

Restricted Maximum Likelihood Estimates of Multilevel Regression Model

A two-level regression model : $$Y_{ij} = \gamma_{00} + \gamma_{10}X_{ij} + \gamma_{01}Z_j + \gamma_{11}X_{ij}Z_j + u_{0j} + u_{1j}X_{ij} + e_{ij}$$ where $e_{ij}\sim N(0,\sigma^2_e)$ and , $$ \...