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return kwic search for rate out of >500 occurrences
286534 occurrences (No.87 in the rank) during 5 years in the PubMed. [no cache] 500 found

350) The key point is to consider this incidence rate as a normal distribution in which both parameters (mean and variance) are modelled differently, depending on whether the system is in an epidemic or non-epidemic phase.

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PMID:21873301 DOI:10.1177/0962280211414853

2015 Statistical methods in medical research

* Bayesian hierarchical Poisson models with a hidden Markov structure for the detection of influenza epidemic outbreaks.

- Considerable effort has been devoted to the development of statistical algorithms for the automated monitoring of influenza surveillance data. In this article, we introduce a framework of models for the early detection of the onset of an influenza epidemic which is applicable to different kinds of surveillance data. In particular, the process of the observed cases is modelled via a Bayesian Hierarchical Poisson model in which the intensity parameter is a function of the incidence rate. The key point is to consider this incidence rate as a normal distribution in which both parameters (mean and variance) are modelled differently, depending on whether the system is in an epidemic or non-epidemic phase. To do so, we propose a hidden Markov model in which the transition between both phases is modelled as a function of the epidemic state of the previous week. Different options for modelling the rates are described, including the option of modelling the mean at each phase as autoregressive processes of order 0, 1 or 2. Bayesian inference is carried out to provide the probability of being in an epidemic state at any given moment. The methodology is applied to various influenza data sets. The results indicate that our methods outperform previous approaches in terms of sensitivity, specificity and timeliness.

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(1)163 of	(9)7 to	(17)3 were	(25)2 may
(2)56 was	(10)6 at	(18)3 without	(26)2 or
(3)44 and	(11)4 as	(19)2 (HR)	(27)2 per
(4)34 null	(12)4 from	(20)2 =	(28)2 product
(5)14 in	(13)4 variability	(21)2 by	(29)2 step
(6)9 is	(14)3 after	(22)2 compared	(30)2 that
(7)8 for	(15)3 coding	(23)2 due	(31)2 under
(8)7 than	(16)3 ranged	(24)2 enzyme	(32)2 which

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--- WordNet output for rate --- =>価格を評定する, 割合, 率, 歩合, 料金, 値段, 相場, 速度, 度合, 人を〜を思う, みなす, 価値がある, 人を〜とみなす, 科金, 評価する Overview of noun rate The noun rate has 4 senses (first 3 from tagged texts) 1. (68) rate -- (a magnitude or frequency relative to a time unit; "they traveled at a rate of 55 miles per hour"; "the rate of change was faster than expected") 2. (39) rate, charge per unit -- (amount of a charge or payment relative to some basis; "a 10-minute phone call at that rate would cost $5") 3. (1) pace, rate -- (the relative speed of progress or change; "he lived at a fast pace"; "he works at a great rate"; "the pace of events accelerated") 4. rate -- (a quantity or amount or measure considered as a proportion of another quantity or amount or measure; "the literacy rate"; "the retention rate"; "the dropout rate") Overview of verb rate The verb rate has 3 senses (first 3 from tagged texts) 1. (9) rate, rank, range, order, grade, place -- (assign a rank or rating to; "how would you rank these students?"; "The restaurant is rated highly in the food guide") 2. (2) rate -- (be worthy of or have a certain rating; "This bond rates highly") 3. (1) rate, value -- (estimate the value of; "How would you rate his chances to become President?"; "Gold was rated highly among the Romans") --- WordNet end ---