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Censoring (statistics)
In statistics, censoring is a condition in which the Value (mathematics), value of a measurement or observation is only partially known. For example, suppose a study is conducted to measure the impact of a drug on mortality rate. In such a study, it may be known that an individual's age at death is ''at least'' 75 years (but may be more). Such a situation could occur if the individual withdrew from the study at age 75, or if the individual is currently alive at the age of 75. Censoring also occurs when a value occurs outside the range of a measuring instrument. For example, a bathroom scale might only measure up to 140 kg, after which it rolls over 0 and continues to count up from there. If a 160 kg individual is weighed using the scale, the observer would only know that the individual's weight is 20 modulo, mod 140 kg (in addition to 160kg, they could weigh 20kg, 300kg, 440kg, and so on). The problem of censored data, in which the observed value of some variable is partially kn ...
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Statistics
Statistics (from German language, German: ', "description of a State (polity), state, a country") is the discipline that concerns the collection, organization, analysis, interpretation, and presentation of data. In applying statistics to a scientific, industrial, or social problem, it is conventional to begin with a statistical population or a statistical model to be studied. Populations can be diverse groups of people or objects such as "all people living in a country" or "every atom composing a crystal". Statistics deals with every aspect of data, including the planning of data collection in terms of the design of statistical survey, surveys and experimental design, experiments. When census data (comprising every member of the target population) cannot be collected, statisticians collect data by developing specific experiment designs and survey sample (statistics), samples. Representative sampling assures that inferences and conclusions can reasonably extend from the sample ...
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Vaccination
Vaccination is the administration of a vaccine to help the immune system develop immunity from a disease. Vaccines contain a microorganism or virus in a weakened, live or killed state, or proteins or toxins from the organism. In stimulating the body's Adaptive immune system, adaptive immunity, they help prevent sickness from an infectious disease. When a sufficiently large percentage of a population has been vaccinated, herd immunity results. Herd immunity protects those who may be immunocompromised and cannot get a vaccine because even a weakened version would harm them. The effectiveness of vaccination has been widely studied and verified. Vaccination is the most effective method of preventing infectious diseases; widespread immunity due to vaccination is largely responsible for the Eradication of infectious diseases, worldwide eradication of smallpox and the elimination of diseases such as polio and tetanus from much of the world. According to the World Health Organization ...
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Maximum Likelihood Estimation
In statistics, maximum likelihood estimation (MLE) is a method of estimation theory, estimating the Statistical parameter, parameters of an assumed probability distribution, given some observed data. This is achieved by Mathematical optimization, maximizing a likelihood function so that, under the assumed statistical model, the Realization (probability), observed data is most probable. The point estimate, point in the parameter space that maximizes the likelihood function is called the maximum likelihood estimate. The logic of maximum likelihood is both intuitive and flexible, and as such the method has become a dominant means of statistical inference. If the likelihood function is Differentiable function, differentiable, the derivative test for finding maxima can be applied. In some cases, the first-order conditions of the likelihood function can be solved analytically; for instance, the ordinary least squares estimator for a linear regression model maximizes the likelihood when ...
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Exponential Distribution
In probability theory and statistics, the exponential distribution or negative exponential distribution is the probability distribution of the distance between events in a Poisson point process, i.e., a process in which events occur continuously and independently at a constant average rate; the distance parameter could be any meaningful mono-dimensional measure of the process, such as time between production errors, or length along a roll of fabric in the weaving manufacturing process. It is a particular case of the gamma distribution. It is the continuous analogue of the geometric distribution, and it has the key property of being memoryless. In addition to being used for the analysis of Poisson point processes it is found in various other contexts. The exponential distribution is not the same as the class of exponential families of distributions. This is a large class of probability distributions that includes the exponential distribution as one of its members, but also includ ...
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Failure Rate
Failure is the social concept of not meeting a desirable or intended objective, and is usually viewed as the opposite of success. The criteria for failure depends on context, and may be relative to a particular observer or belief system. One person might consider a failure what another person considers a success, particularly in cases of direct competition or a zero-sum game. Similarly, the degree of success or failure in a situation may be differently viewed by distinct observers or participants, such that a situation that one considers to be a failure, another might consider to be a success, a qualified success or a neutral situation. It may also be difficult or impossible to ascertain whether a situation meets criteria for failure or success due to ambiguous or ill-defined definition of those criteria. Finding useful and effective criteria or heuristics to judge the success or failure of a situation may itself be a significant task. Sociology Cultural historian Sco ...
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Survival Function
The survival function is a function that gives the probability that a patient, device, or other object of interest will survive past a certain time. The survival function is also known as the survivor function or reliability function. The term ''reliability function'' is common in engineering while the term ''survival function'' is used in a broader range of applications, including human mortality. The survival function is the complementary cumulative distribution function of the lifetime. Sometimes complementary cumulative distribution functions are called survival functions in general. Definition Let the lifetime T be a continuous random variable describing the time to failure. If T has cumulative distribution function F(t) and probability density function f(t) on the interval [0,\infty), then the ''survival function'' or ''reliability function'' is: S(t) = P(T > t) = 1-F(t) = 1 - \int_0^t f(u)\,du Examples of survival functions The graphs below show examples of hypot ...
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Likelihood Function
A likelihood function (often simply called the likelihood) measures how well a statistical model explains observed data by calculating the probability of seeing that data under different parameter values of the model. It is constructed from the joint probability distribution of the random variable that (presumably) generated the observations. When evaluated on the actual data points, it becomes a function solely of the model parameters. In maximum likelihood estimation, the argument that maximizes the likelihood function serves as a point estimate for the unknown parameter, while the Fisher information (often approximated by the likelihood's Hessian matrix at the maximum) gives an indication of the estimate's precision. In contrast, in Bayesian statistics, the estimate of interest is the ''converse'' of the likelihood, the so-called posterior probability of the parameter given the observed data, which is calculated via Bayes' rule. Definition The likelihood function, ...
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James Tobin
James Tobin (March 5, 1918 – March 11, 2002) was an American economist who served on the Council of Economic Advisers and consulted with the Board of Governors of the Federal Reserve System, and taught at Harvard University, Harvard and Yale University, Yale Universities. He contributed to the development of key ideas in the Keynesian economics of his generation and advocated government intervention in particular to stabilize output and avoid recessions. His academic work included pioneering contributions to the study of investment (macroeconomics), investment, monetary and fiscal policy and financial markets. He also proposed an econometric model for Censoring (statistics), censored dependent variables, the well-known tobit model. Along with fellow Neo-Keynesian economics, neo-Keynesian economist James Meade in 1977, Tobin proposed Nominal income target, nominal GDP targeting as a Discretionary policy, monetary policy rule in 1980. Tobin received the Nobel Memorial Prize in Econ ...
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Tobit Model
In statistics, a tobit model is any of a class of regression models in which the observed range of the dependent variable is censored in some way. The term was coined by Arthur Goldberger in reference to James Tobin, who developed the model in 1958 to mitigate the problem of zero-inflated data for observations of household expenditure on durable goods. Because Tobin's method can be easily extended to handle truncated and other non-randomly selected samples, some authors adopt a broader definition of the tobit model that includes these cases. Tobin's idea was to modify the likelihood function so that it reflects the unequal sampling probability for each observation depending on whether the latent dependent variable fell above or below the determined threshold. For a sample that, as in Tobin's original case, was censored from below at zero, the sampling probability for each non-limit observation is simply the height of the appropriate density function. For any limit observatio ...
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Censored Regression Model
Censored regression models are a class of models in which the dependent variable is censored above or below a certain threshold. A commonly used likelihood-based model to accommodate to a censored sample is the Tobit model, but quantile In statistics and probability, quantiles are cut points dividing the range of a probability distribution into continuous intervals with equal probabilities or dividing the observations in a sample in the same way. There is one fewer quantile t ... and Nonparametric regression, nonparametric estimators have also been developed. These and other censored regression models are often confused with truncated regression models. Truncated regression models are used for data where whole observations are missing so that the values for the dependent and the independent variables are unknown. Censored regression models are used for data where only the value for the dependent variable is unknown while the values of the independent variables are still avail ...
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Censored Data Example
Censorship is the suppression of speech, public communication, or other information. This may be done on the basis that such material is considered objectionable, harmful, sensitive, or "inconvenient". Censorship can be conducted by governments and private institutions. When an individual such as an author or other creator engages in censorship of their own works or speech, it is referred to as ''self-censorship''. General censorship occurs in a variety of different media, including speech, books, music, films, and other arts, the press, radio, television, and the Internet for a variety of claimed reasons including national security, to control obscenity, pornography, and hate speech, to protect children or other vulnerable groups, to promote or restrict political or religious views, and to prevent slander and libel. Specific rules and regulations regarding censorship vary between legal jurisdictions and/or private organizations. History Socrates, while defying attempts b ...
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ClinicoEconomics And Outcomes Research
''ClinicoEconomics and Outcomes Research '' is a peer-reviewed healthcare journal focusing on covering the economic impact of health policy and health systems organization. The journal was established in 2009 and is published by Dove Medical Press Dove Medical Press is an academic publisher of open-access peer-reviewed scientific and medical journals, with offices in Macclesfield, London (United Kingdom); Princeton, New Jersey (United States); and Auckland (New Zealand). In September 2017, .... External links * English-language journals Open access journals Dove Medical Press academic journals Healthcare journals Academic journals established in 2009 {{med-journal-stub ...
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