HIV & AIDS

England on track to eliminate HIV transmission by 2030

The annual number of new HIV infections among men who have sex with men in England is likely to have fallen dramatically, from 2,770 in 2013 to 854 in 2018, showing elimination of HIV transmission by 2030 to be within reach—suggests ...

Diseases, Conditions, Syndromes

Diabetics hit harder by COVID-19

People with type 2 diabetes are at significantly elevated risk of needing intensive care if they get COVID-19. This is shown by a study comprising data on 2.6 million Swedes, of whom half a million are on the diabetes register. ...

Oncology & Cancer

Predicting mutated gene associated with melanoma

Although risk for melanoma, the most serious type of skin cancer, is often associated with ultraviolet light exposure, genetic factors are also at play, with some families being more prone to the disease than others.

Health

Does a vegan diet lead to poorer bone health?

The vegan diet is trending currently. How this type of diet affects health is the subject of scientific studies. In a new study from the German Federal Institute for Risk Assessment (BfR), the bone health of 36 vegans as ...

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Statistical model

A statistical model is a set of mathematical equations which describe the behavior of an object of study in terms of random variables and their associated probability distributions. If the model has only one equation it is called a single-equation model, whereas if it has more than one equation, it is known as a multiple-equation model.

In mathematical terms, a statistical model is frequently thought of as a pair (Y,P) where Y is the set of possible observations and P the set of possible probability distributions on Y. It is assumed that there is a distinct element of P which generates the observed data. Statistical inference enables us to make statements about which element(s) of this set are likely to be the true one.

Three notions are sufficient to describe all statistical models.

One of the most basic models is the simple linear regression model which assumes a relationship between two random variables Y and X. For instance, one may want to linearly explain child mortality in a given country by its GDP. This is a statistical model because the relationship need not to be perfect and the model includes a disturbance term which accounts for other effects on child mortality other than GDP.

As a second example, Bayes theorem in its raw form may be intractable, but assuming a general model H allows it to become

which may be easier. Models can also be compared using measures such as Bayes factors or mean square error.

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