ELIZA

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566982 occurrences (No.17 in the rank) during 5 years in the PubMed. [no cache] 500 found

393) In this study, we developed a new likelihood-based approach wherein the likelihood function is integrated over random effects to obtain a marginal likelihood function.

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PMID:22143404 DOI:10.1177/0962280211430681

2015 Statistical methods in medical research

* Slope estimation for informatively right censored longitudinal data modelling the number of observations using geometric and Poisson distributions: application to renal transplant cohort.

- Analysis of longitudinal data is often complicated by the presence of informative right censoring. This type of censoring should be accounted for in the analysis so that valid slope estimates are attained. In this study, we developed a new likelihood-based approach wherein the likelihood function is integrated over random effects to obtain a marginal likelihood function. Maximum likelihood estimates for the population slope were acquired by direct maximisation of the marginal likelihood function and empirical Bayes estimates for the individual slopes were generated using Gaussian quadrature. The performance of the model was assessed using the geometric and Poisson distributions to model the number of observations for every individual subject. Our model generated valid estimates for the slopes under both distributions with minimal bias and mean squared errors. Our sensitivity analysis confirmed the robustness of the model to assumptions pertaining to the underlying distribution and demonstrated its insensitivity to normality assumptions. Moreover, superiority of the model in terms of accuracy of slope estimates was consistently shown across the different levels of censoring in comparison to the naïve and bootstrap approaches. This model was illustrated using the cohort of renal transplant patients and estimates of the slopes that are adjusted for informative right censoring were acquired.

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(1)251 of	(8)5 to	(15)3 that	(22)2 models
(2)52 on	(9)4 are	(16)3 with	(23)2 observed
(3)29 null	(10)4 such	(17)2 at	(24)2 regression
(4)22 in	(11)3 between	(18)2 due	(25)2 through
(5)16 and	(12)3 from	(19)2 has
(6)13 were	(13)3 induced	(20)2 include
(7)7 for	(14)3 may	(21)2 limited

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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 ---