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Utility Assessment
Utility assessment, also called utility measurement, is a process by which the utility function of individuals or groups can be estimated. There are many different methods for utility assessment. Assessing single-attribute utility functions A single-attribute utility function maps the amount of money a person has (or gains), to a number representing the subjective satisfaction he derives from it. The motivation to define a utility function comes from the St. Petersburg paradox: the observation that people are not willing to pay much for a lottery, even if its expected monetary gain is infinite. The classical solution to this paradox, suggested by Daniel Bernoulli and Gabriel Cramer, is that most people have a utility function that is strictly concave, and they aim to maximize their expected utility, rather than their expected gain. Power-log utility Bernouli himself assumed that the utility is logarithmic, that is, u(''x'')=log(''x'') where x is the amount of money; this was s ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Utility Function
In economics, utility is a measure of a certain person's satisfaction from a certain state of the world. Over time, the term has been used with at least two meanings. * In a Normative economics, normative context, utility refers to a goal or objective that we wish to maximize, i.e., an objective function. This kind of utility bears a closer resemblance to the original Utilitarianism, utilitarian concept, developed by moral philosophers such as Jeremy Bentham and John Stuart Mill. * In a Positive economics, descriptive context, the term refers to an ''apparent'' objective function; such a function is Revealed preference, revealed by a person's behavior, and specifically by their preferences over Lottery (decision theory), lotteries, which can be any quantified choice. The relationship between these two kinds of utility functions has been a source of controversy among both Economics, economists and Ethics, ethicists, with most maintaining that the two are distinct but generally re ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Confounding
In causal inference, a confounder is a variable that influences both the dependent variable and independent variable, causing a spurious association. Confounding is a causal concept, and as such, cannot be described in terms of correlations or associations.Pearl, J., (2009). Simpson's Paradox, Confounding, and Collapsibility In ''Causality: Models, Reasoning and Inference'' (2nd ed.). New York : Cambridge University Press. The existence of confounders is an important quantitative explanation why correlation does not imply causation. Some notations are explicitly designed to identify the existence, possible existence, or non-existence of confounders in causal relationships between elements of a system. Confounders are threats to internal validity. Example Let's assume that a trucking company owns a fleet of trucks made by two different manufacturers. Trucks made by one manufacturer are called "A Trucks" and trucks made by the other manufacturer are called "B Trucks." ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Experimental Design
The design of experiments (DOE), also known as experiment design or experimental design, is the design of any task that aims to describe and explain the variation of information under conditions that are hypothesized to reflect the variation. The term is generally associated with experiments in which the design introduces conditions that directly affect the variation, but may also refer to the design of quasi-experiments, in which natural conditions that influence the variation are selected for observation. In its simplest form, an experiment aims at predicting the outcome by introducing a change of the preconditions, which is represented by one or more independent variables, also referred to as "input variables" or "predictor variables." The change in one or more independent variables is generally hypothesized to result in a change in one or more dependent variables, also referred to as "output variables" or "response variables." The experimental design may also identify c ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Discrete Choice
In economics, discrete choice models, or qualitative choice models, describe, explain, and predict choices between two or more discrete alternatives, such as entering or not entering the labor market, or choosing between modes of transport. Such choices contrast with standard consumption models in which the quantity of each good consumed is assumed to be a continuous variable. In the continuous case, calculus methods (e.g. first-order conditions) can be used to determine the optimum amount chosen, and demand can be modeled empirically using regression analysis. On the other hand, discrete choice analysis examines situations in which the potential outcomes are discrete, such that the optimum is not characterized by standard first-order conditions. Thus, instead of examining "how much" as in problems with continuous choice variables, discrete choice analysis examines "which one". However, discrete choice analysis can also be used to examine the chosen quantity when only a few distinc ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Time Trade-off
In health economics, time trade-off (TTO) is a technique used to measure the quality of life that a person or group is experiencing. An individual will be presented with a set of directions such as: Imagine that you are told that you have 10 years left to live. In connection with this you are also told that you can choose to live these 10 years in your current health state or that you can choose to give up some life years to live for a shorter period in full health. Indicate with a cross on the line the number of years in full health that you think is of equal value to 10 years in your current health state. The answer given by the individual shows how many years in the current health state they would be willing to 'trade off', in order to regain full health. This answer can be used to calculate the individual's quality of life in that health state. For example, an individual with severe asthma could be offered 10 years in their current condition, or a shorter length of time in ful ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
EQ-5D
EQ-5D is a standardised measure of health-related quality of life developed by thEuroQol Groupto provide a simple, generic questionnaire for use in clinical and economic appraisal and population health surveys. EQ-5D assesses health status in terms of five dimensions of health and is considered a 'generic' questionnaire because these dimensions are not specific to any one patient group or health condition. EQ-5D can also be referred to as a patient-reported outcome (PRO) measure, because patients can complete the questionnaire themselves to provide information about their current health status and how this changes over time. 'EQ-5D' is not an abbreviation and is the correct term to use when referring to the instrument in general. EQ-5D is widely used around the world in clinical trials and real-world clinical settings, population studies, and health economic evaluations. By mid-2020, the number of EQ-5D studies registered with the EuroQol Group totalled over 39,000. These comprised ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Quality-adjusted Life Year
The quality-adjusted life year (QALY) is a generic measure of disease burden, including both the quality and the quantity of life lived. It is used in economic evaluation to assess the value of medical interventions. One QALY equates to one year in perfect health. QALY scores range from 1 (perfect health) to 0 (dead). QALYs can be used to inform health insurance coverage determinations, treatment decisions, to evaluate programs, and to set priorities for future programs. Critics argue that the QALY oversimplifies how actual patients would assess risks and outcomes, and that its use may restrict patients with disabilities from accessing treatment. Proponents of the measure acknowledge that the QALY has some shortcomings, but that its ability to quantify tradeoffs and opportunity costs from the patient, and societal perspective make it a critical tool for equitably allocating resources. Calculation A measure of the state of health of a person or group in which the benefits, in ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Health Economics
Health economics is a branch of economics concerned with issues related to Health care efficiency, efficiency, effectiveness, value and behavior in the production and consumption of health and healthcare. Health economics is important in determining how to improve health outcomes and lifestyle patterns through interactions between individuals, healthcare providers and clinical settings. Health economists study the functioning of healthcare systems and health-affecting behaviors such as smoking, diabetes, and obesity. One of the biggest difficulties regarding healthcare economics is that it does not follow normal rules for economics. Price and quality are often hidden by the third-party payer system of insurance companies and employers. Additionally, Quality-adjusted life year, QALYs (Quality Adjusted Life Years), one of the most commonly used measurements for treatments, is very difficult to measure and relies upon assumptions that are often unreasonable. A seminal 1963 arti ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Ordinal Utility
In economics, an ordinal utility function is a function representing the preferences of an agent on an ordinal scale. Ordinal utility theory claims that it is only meaningful to ask which option is better than the other, but it is meaningless to ask ''how much'' better it is or how good it is. All of the theory of consumer decision-making under conditions of certainty can be, and typically is, expressed in terms of ordinal utility. For example, suppose George tells us that "I prefer A to B and B to C". George's preferences can be represented by a function ''u'' such that: :u(A)=9, u(B)=8, u(C)=1 But critics of cardinal utility claim the only meaningful message of this function is the order u(A)>u(B)>u(C); the actual numbers are meaningless. Hence, George's preferences can also be represented by the following function ''v'': :v(A)=9, v(B)=2, v(C)=1 The functions ''u'' and ''v'' are ordinally equivalent – they represent George's preferences equally well. Ordinal utility contrast ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Eugene Galanter
Eugene Galanter (1924–2016) was one of the modern founders of cognitive psychology. He was an academic in the field of experimental psychology and an author. Dr. Galanter was Professor Emeritus of Psychology and Quondam Director of the Psychophysics Laboratory at Columbia University. He was also the co-founder, Chairman of the Board of Directors and Chief Scientific Officer of Children’s Progress, an award-winning New York City-based company that specializes in the use of computer technology in early education. The company's assessments and reports have been used in 40 states and 9 countries. Biography After serving in the United States Armed Forces in World War II, Galanter attended Swarthmore College, receiving an Honors B.A. in 1950. He went on to graduate school in psychology at the University of Pennsylvania and after receiving his Ph.D. in 1953, he was appointed Assistant Professor of Mathematical Psychology in the University of Pennsylvania's Department of Psycholog ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Loss Aversion
In cognitive science and behavioral economics, loss aversion refers to a cognitive bias in which the same situation is perceived as worse if it is framed as a loss, rather than a gain. It should not be confused with risk aversion, which describes the rational behavior of valuing an uncertain outcome at less than its expected value. When defined in terms of the pseudo-utility function as in cumulative prospect theory (CPT), the left-hand of the function increases much more steeply than gains, thus being more "painful" than the satisfaction from a comparable gain. Empirically, losses tend to be treated as if they were twice as large as an equivalent gain. Loss aversion was first proposed by Amos Tversky and Daniel Kahneman as an important component of prospect theory. History In 1979, Daniel Kahneman and his associate Amos Tversky originally coined the term "loss aversion" in their initial proposal of prospect theory as an alternative descriptive model of decision makin ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
