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Observational Study
In fields such as epidemiology, social sciences, psychology and statistics, an observational study draws inferences from a sample (statistics), sample to a statistical population, population where the dependent and independent variables, independent variable is not under the Scientific control, control of the researcher because of ethical concerns or logistical constraints. One common observational study is about the possible effect of a treatment on subjects, where the assignment of subjects into a treated group versus a control group is outside the control of the investigator. This is in contrast with experiments, such as randomized controlled trials, where each subject is Random assignment, randomly assigned to a treated group or a control group. Observational studies, for lacking an assignment mechanism, naturally present difficulties for inferential analysis. Motivation The independent variable may be beyond the control of the investigator for a variety of reasons: * A rand ...
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External Validity
External validity is the validity of applying the conclusions of a scientific study outside the context of that study. In other words, it is the extent to which the results of a study can generalize or transport to other situations, people, stimuli, and times.Aronson, E., Wilson, T. D., Akert, R. M., & Fehr, B. (2007). Social psychology. (4 ed.). Toronto, ON: Pearson Education. Generalizability refers to the applicability of a predefined sample to a broader population while transportability refers to the applicability of one sample to another target population. In contrast, internal validity is the validity of conclusions drawn ''within'' the context of a particular study. Mathematical analysis of external validity concerns a determination of whether generalization across heterogeneous populations is feasible, and devising statistical and computational methods that produce valid generalizations. In establishing external validity, scholars tend to identify the "scope" of the study ...
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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." ...
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Propensity Score Matching
In the statistical analysis of observational data, propensity score matching (PSM) is a statistical matching technique that attempts to estimate the effect of a treatment, policy, or other intervention by accounting for the covariates that predict receiving the treatment. PSM attempts to reduce the bias due to confounding variables that could be found in an estimate of the treatment effect obtained from simply comparing outcomes among units that received the treatment versus those that did not. Paul R. Rosenbaum and Donald Rubin introduced the technique in 1983, defining the propensity score as the conditional probability of a unit (e.g., person, classroom, school) being assigned to the treatment, given a set of observed covariates. The possibility of bias arises because a difference in the treatment outcome (such as the average treatment effect) between treated and untreated groups may be caused by a factor that predicts treatment rather than the treatment itself. In ra ...
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Matching (statistics)
Matching is a statistical technique that evaluates the effect of a treatment by comparing the treated and the non-treated units in an observational study or quasi-experiment (i.e. when the treatment is not randomly assigned). The goal of matching is to reduce bias for the estimated treatment effect in an observational-data study, by finding, for every treated unit, one (or more) non-treated unit(s) with similar observable characteristics against which the covariates are balanced out (similar to the K-nearest neighbors algorithm). By matching treated units to similar non-treated units, matching enables a comparison of outcomes among treated and non-treated units to estimate the effect of the treatment reducing bias due to confounding. Propensity score matching, an early matching technique, was developed as part of the Rubin causal model, but has been shown to increase model dependence, bias, inefficiency, and power and is no longer recommended compared to other matching methods. A si ...
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Healthcare
Health care, or healthcare, is the improvement or maintenance of health via the preventive healthcare, prevention, diagnosis, therapy, treatment, wikt:amelioration, amelioration or cure of disease, illness, injury, and other disability, physical and mental impairments in people. Health care is delivered by health professionals and allied health professions, allied health fields. Medicine, dentistry, pharmacy, midwifery, nursing, optometry, audiology, psychology, occupational therapy, physical therapy, athletic training, and other health professions all constitute health care. The term includes work done in providing primary care, wikt:secondary care, secondary care, tertiary care, and public health. Access to health care may vary across countries, communities, and individuals, influenced by social and economic conditions and health policy, health policies. Providing health care services means "the timely use of personal health services to achieve the best possible health outcom ...
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Multivariate Statistics
Multivariate statistics is a subdivision of statistics encompassing the simultaneous observation and analysis of more than one outcome variable, i.e., '' multivariate random variables''. Multivariate statistics concerns understanding the different aims and background of each of the different forms of multivariate analysis, and how they relate to each other. The practical application of multivariate statistics to a particular problem may involve several types of univariate and multivariate analyses in order to understand the relationships between variables and their relevance to the problem being studied. In addition, multivariate statistics is concerned with multivariate probability distributions, in terms of both :*how these can be used to represent the distributions of observed data; :*how they can be used as part of statistical inference, particularly where several different quantities are of interest to the same analysis. Certain types of problems involving multivariate da ...
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Bias
Bias is a disproportionate weight ''in favor of'' or ''against'' an idea or thing, usually in a way that is inaccurate, closed-minded, prejudicial, or unfair. Biases can be innate or learned. People may develop biases for or against an individual, a group, or a belief. In science and engineering, a bias is a systematic error. Statistical bias results from an unfair sampling of a population, or from an estimation process that does not give accurate results on average. Etymology The word appears to derive from Old Provençal into Old French ''biais'', "sideways, askance, against the grain". Whence comes French ''biais'', "a slant, a slope, an oblique". It seems to have entered English via the game of bowls">English (language)">English via the game of bowls, where it referred to balls made with a greater weight on one side. Which expanded to the figurative use, "a one-sided tendency of the mind", and, at first especially in law, "undue propensity or prejudice". or ballast, ...
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National Center For Complementary And Integrative Health
The National Center for Complementary and Integrative Health (NCCIH) is a United States government agency which explores complementary and alternative medicine (CAM). It was created in 1991 as the Office of Alternative Medicine (OAM), and renamed the National Center for Complementary and Alternative Medicine (NCCAM) before receiving its current name in 2014. NCCIH is one of the 27 institutes and centers that make up the National Institutes of Health (NIH) within the United States Department of Health and Human Services. NCCIH has been criticized for funding and marketing pseudoscientific medicine. Organization and history Overview The Office of Alternative Medicine (OAM) was established in October 1991 by the United States Congress. The OAM was expanded from an office into a center and renamed the National Center for Complementary and Alternative Medicine (NCCAM) in October 1998. It is one of several centers within the National Institutes of Health (NIH). The founding ...
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Panel Analysis
Panel (data) analysis is a statistical method, widely used in social science, epidemiology, and econometrics to analyze two-dimensional (typically cross sectional and longitudinal) panel data. The data are usually collected over time and over the same individuals and then a regression is run over these two dimensions. Multidimensional analysis is an econometric method in which data are collected over more than two dimensions (typically, time, individuals, and some third dimension). A common panel data regression model looks like y_=a+bx_+\varepsilon_, where y is the dependent variable, x is the independent variable, a and b are coefficients, i and t are indices for individuals and time. The error \varepsilon_ is very important in this analysis. Assumptions about the error term determine whether we speak of fixed effects or random effects. In a fixed effects model, \varepsilon_ is assumed to vary non-stochastically over i or t making the fixed effects model analogous to a dummy va ...
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Cohort Study
A cohort study is a particular form of longitudinal study that samples a Cohort (statistics), cohort (a group of people who share a defining characteristic, typically those who experienced a common event in a selected period, such as birth or graduation), performing a Cross-sectional data, cross-section at intervals through time. It is a type of panel study where the individuals in the panel share a common characteristic. Cohort studies represent one of the fundamental designs of epidemiology which are used in research in the fields of medicine, pharmacy, nursing, Psychological research, psychology, social science, and in any field reliant on 'difficult to reach' answers that are based on evidence (statistics). In medicine for instance, while clinical trials are used primarily for assessing the safety of newly developed pharmaceuticals before they are approved for sale, epidemiological analysis on how risk factors affect the incidence of diseases is often used to identify the caus ...
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Study Of Global Communication
The study of global communication is an interdisciplinarity, interdisciplinary field focusing on international communication, global communication, or the ways that people connect, share, relate, and mobilize across geographic, political, economic, social, and cultural divides. Global communication implies a transfer of knowledge and ideas from centers of power to peripheries and the imposition of a new intercultural communication, intercultural hegemony by means of the "soft power" of global news and entertainment... "International" Or "Global" With the end of the twentieth century and the turn of a new millennium, the global arena and the field of international communication were undergoing significant changes. Some authors started to use the term global communication because it goes beyond the bounds of individual states and emphasizes communication between and among peoples across borders and, importantly, the rise of transnational media corporations. International communicatio ...
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