ELIZA

return kwic search for effects out of >500 occurrences
566982 occurrences (No.17 in the rank) during 5 years in the PubMed. [cache]

372) The multivariate t distribution is desired for heavy-tailed random effects and converges to the multivariate normal distribution when the degrees of freedom go to infinity.

--- ABSTRACT ---

PMID:33846992 DOI:10.1002/sim.8983

2021 Statistics in medicine

* Bayesian network meta-regression hierarchical models using heavy-tailed multivariate random effects with covariate-dependent variances.

- Network meta-analysis (NMA) is gaining popularity in evidence synthesis and network meta-regression allows us to incorporate potentially important covariates into network meta-analysis. In this article, we propose a Bayesian network meta-regression hierarchical model and assume a general multivariate t distribution for the random treatment effects. The multivariate t distribution is desired for heavy-tailed random effects and converges to the multivariate normal distribution when the degrees of freedom go to infinity. Moreover, in NMA, some treatments are compared only in a single study. To overcome such sparsity, we propose a log-linear regression model for the variances of the random effects and incorporate aggregate covariates into modeling the variance components. We develop a Markov chain Monte Carlo sampling algorithm to sample from the posterior distribution via the collapsed Gibbs technique. We further use the deviance information criterion and the logarithm of the pseudo-marginal likelihood for model comparison. A simulation study is conducted and a detailed analysis from our motivating case study is carried out to further demonstrate the proposed methodology.

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(1)230 of	(8)6 between	(15)3 may	(22)2 from
(2)71 on	(9)6 such	(16)3 model	(23)2 meta-analysis
(3)34 null	(10)5 is	(17)3 that	(24)2 or
(4)22 in	(11)3 at	(18)3 with	(25)2 reported
(5)12 were	(12)3 but	(19)2 against
(6)11 and	(13)3 by	(20)2 as
(7)10 are	(14)3 can	(21)2 for

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--- WordNet output for effects --- =>個人資産 Overview of noun effects The noun effects has 1 sense (no senses from tagged texts) 1. effects, personal effects -- (property of a personal character that is portable but not used in business; "she left some of her personal effects in the house"; "I watched over their effects until they returned") Overview of noun effect The noun effect has 6 senses (first 5 from tagged texts) 1. (101) consequence, effect, outcome, result, event, issue, upshot -- (a phenomenon that follows and is caused by some previous phenomenon; "the magnetic effect was greater when the rod was lengthwise"; "his decision had depressing consequences for business"; "he acted very wise after the event") 2. (11) impression, effect -- (an outward appearance; "he made a good impression"; "I wanted to create an impression of success"; "she retained that bold effect in her reproductions of the original painting") 3. (9) effect -- (an impression (especially one that is artificial or contrived); "he just did it for effect") 4. (2) effect, essence, burden, core, gist -- (the central meaning or theme of a speech or literary work) 5. (1) effect, force -- ((of a law) having legal validity; "the law is still in effect") 6. effect -- (a symptom caused by an illness or a drug; "the effects of sleep loss"; "the effect of the anesthetic") Overview of verb effect The verb effect has 2 senses (first 2 from tagged texts) 1. (17) effect, effectuate, set up -- (produce; "The scientists set up a shock wave") 2. (3) effect -- (act so as to bring into existence; "effect a change") --- WordNet end ---