[R-meta] When to remove the intercept and other questions

[Rafael Rios]

Thank you for the help, Dr. Wofgang!

Best wishes,

Rafael Rios Moura.
*scientia amabilis*

PhD in Ecology and Conservation
Postdoctoral Researcher
Universidade Estadual de Campinas (UNICAMP)
Campinas, São Paulo, Brazil
________________________________________________________
ORCID: http://orcid.org/0000-0002-7911-4734
Research Gate: https://www.researchgate.net/profile/Rafael_Rios_Moura2
Currículo Lattes:
http://buscatextual.cnpq.br/buscatextual/visualizacv.do?id=K4244908A8

<http://buscatextual.cnpq.br/buscatextual/visualizacv.do?id=K4244908A8>

2018-05-20 14:28 GMT-03:00 Viechtbauer, Wolfgang (SP) <
wolfgang.viechtbauer at maastrichtuniversity.nl>:

> Dear Rafael,
>
> Please always cc the mailing list.
>
> Since your question is about the fixed effects part of the model, whether
> you are fitting a model with rma() or rma.mv() doesn't change how one
> deals with categorical moderators (or a combination of categorical and
> continuous ones). So, while those links lead to discussions of models
> fitted with rma(), the underlying principles are the same.
>
> Best,
> Wolfgang
>
> -----Original Message-----
> From: Rafael Rios [mailto:biorafaelrm at gmail.com]
> Sent: Saturday, 19 May, 2018 19:40
> To: Viechtbauer, Wolfgang (SP)
> Subject: Re: When to remove the intercept and other questions
>
> Dear Wolfgang,
>
> Thank you a lot for the quick answer. If I understood correctly, the test
> with intercept term is used to evaluate if the mean effect size for each
> subgroup of the categorical predictor is the same. However, when I remove
> the intercept, I am testing if each mean outcome is 0. Thus, I need to use
> the intercept in my meta-analytic models, because I want to compare
> outcome differences between subgroups of the moderator.
>
> Your links with examples about how to calculate differences
> between subgroups will be helpful too, but my doubt is related to a
> different model. I am using rma.mv function with R argument to control
> for phylogenetic non-independence among effect sizes. The moderators are a
> categorical variable (with four subgroups) and a continuous one.
> Consequetly, I will obtain four straghts. I need intercept and
> slope values for each straight line to plot in a graph. How can I obtain
> such information?
>
> Best wishes,
>
> Rafael.
>
> Em sáb, 19 de mai de 2018 12:02, Viechtbauer, Wolfgang (SP) <
> wolfgang.viechtbauer at maastrichtuniversity.nl> escreveu:
> Dear Rafael,
>
> Let's take a simple example:
>
> ### load BCG vaccine data
> dat <- get(data(dat.bcg))
>
> ### calculate log risk ratios and corresponding sampling variances
> dat <- escalc(measure="RR", ai=tpos, bi=tneg, ci=cpos, di=cneg,
> data=dat.bcg)
> dat
>
> ### mixed-effects meta-regression model with categorical moderator
> res <- rma(yi, vi, mods = ~ alloc, data=dat)
> res
>
> You will find:
>
> Test of Moderators (coefficients 2:3):
> QM(df = 2) = 1.7675, p-val = 0.4132
>
> Model Results:
>
>                  estimate      se     zval    pval    ci.lb   ci.ub
> intrcpt           -0.5180  0.4412  -1.1740  0.2404  -1.3827  0.3468
> allocrandom       -0.4478  0.5158  -0.8682  0.3853  -1.4588  0.5632
> allocsystematic    0.0890  0.5600   0.1590  0.8737  -1.0086  1.1867
>
> The QM-test tests coefficients 2 and 3, which are the *differences*
> between the reference level (in this case 'alternate') and the other two
> levels ('random' and 'systematic'). So, this gives you a test whether the
> mean outcome is the same for the three levels.
>
> ### model with intercept removed
> res <- rma(yi, vi, mods = ~ alloc - 1, data=dat)
> res
>
> You will find:
>
> Test of Moderators (coefficients 1:3):
> QM(df = 3) = 15.9842, p-val = 0.0011
>
> Model Results:
>
>                  estimate      se     zval    pval    ci.lb    ci.ub
> allocalternate    -0.5180  0.4412  -1.1740  0.2404  -1.3827   0.3468
> allocrandom       -0.9658  0.2672  -3.6138  0.0003  -1.4896  -0.4420  ***
> allocsystematic   -0.4289  0.3449  -1.2434  0.2137  -1.1050   0.2472
>
> In this case, the coefficients are the mean outcomes for each level. The
> QM-test tests coefficients 1, 2, and 3, so it tests whether the mean
> outcome is 0 for all three levels.
>
> You might also want to work through these examples:
>
> http://www.metafor-project.org/doku.php/tips:testing_factors_lincoms
> http://www.metafor-project.org/doku.php/tips:multiple_factors_interactions
>
> Best,
> Wolfgang
>
> -----Original Message-----
> From: Rafael Rios [mailto:biorafaelrm at gmail.com]
> Sent: Saturday, 19 May, 2018 3:57
> To: r-sig-meta-analysis at r-project.org; Viechtbauer, Wolfgang (SP)
> Subject: When to remove the intercept and other questions
>
> Dear Dr. Wolfgang and All,
>
> I have some doubts that you could help me to clarify. I read e-mails in
> R-meta list of a conversation between Samuel Knapp and James Pustejovsky
> with the title "Testing of moderators in rma()". James clarified the
> following:
>
> "When the model includes an intercept term, the omnibus test does *not*
> include the intercept. So the null hypothesis is b1 = 0 and b2 =0.
>
> If you fit the model without the intercept, then the equivalent to the
> omnibus test from the model with an intercept would be that the average
> effect sizes are all equal, as in b1 = b2 = b3."
>
> I want to compare the differences between effect sizes of four subgroups
> from a categorical moderator. According James, I should remove the
> intercept from the meta-analysis. I have had different results including or
> removing the intercept. That is why I am insecure about to use this
> approach. What do you think? Is it reasonable to remove the intercept in my
> case?
>
> I also have some questions about how to obtain the intercept and slope
> from multi-level meta-analysis with two moderators, a categorical moderator
> and a continuous). How can I estimate the intercept and slope of each
> subgroup to include the straights in a graph.
>
> Every help is welcome!
>
> Best wishes,
>
> Rafael Rios Moura.
> scientia amabilis
>
> PhD in Ecology and Conservation
> Postdoctoral Researcher
> Universidade Estadual de Campinas (UNICAMP)
> Campinas, São Paulo, Brazil
> ________________________________________________________
> ORCID: http://orcid.org/0000-0002-7911-4734
> Research Gate: https://www.researchgate.net/profile/Rafael_Rios_Moura2
> Currículo Lattes: http://buscatextual.cnpq.br/buscatextual/
> visualizacv.do?id=K4244908A8
>

	[[alternative HTML version deleted]]