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Marginal Structural Models
Marginal structural models are a class of statistical models used for causal inference in epidemiology. Such models handle the issue of time-dependent confounding in evaluation of the efficacy of interventions by inverse probability weighting for receipt of treatment, they allow us to estimate the average causal effects. For instance, in the study of the effect of zidovudine in AIDS-related mortality, CD4 lymphocyte is used both for treatment indication, is influenced by treatment, and affects survival. Time-dependent confounders are typically highly prognostic of health outcomes and applied in dosing or indication for certain therapies, such as body weight or lab values such as alanine aminotransferase or bilirubin. The first marginal structural models were introduced in 2000. The works of James Robins James M. Robins is an epidemiologist and biostatistician best known for advancing methods for drawing causal inferences from complex observational studies and randomized tr ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Statistical Model
A statistical model is a mathematical model that embodies a set of statistical assumptions concerning the generation of Sample (statistics), sample data (and similar data from a larger Statistical population, population). A statistical model represents, often in considerably idealized form, the data-generating process. A statistical model is usually specified as a mathematical relationship between one or more random variables and other non-random variables. As such, a statistical model is "a formal representation of a theory" (Herman J. Adèr, Herman Adèr quoting Kenneth A. Bollen, Kenneth Bollen). All Statistical hypothesis testing, statistical hypothesis tests and all Estimator, statistical estimators are derived via statistical models. More generally, statistical models are part of the foundation of statistical inference. Introduction Informally, a statistical model can be thought of as a statistical assumption (or set of statistical assumptions) with a certain property: that ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Causal Inference
Causal inference is the process of determining the independent, actual effect of a particular phenomenon that is a component of a larger system. The main difference between causal inference and inference of association is that causal inference analyzes the response of an effect variable when a cause of the effect variable is changed. The science of why things occur is called etiology. Causal inference is said to provide the evidence of causality theorized by causal reasoning. Causal inference is widely studied across all sciences. Several innovations in the development and implementation of methodology designed to determine causality have proliferated in recent decades. Causal inference remains especially difficult where experimentation is difficult or impossible, which is common throughout most sciences. The approaches to causal inference are broadly applicable across all types of scientific disciplines, and many methods of causal inference that were designed for certain discipl ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Epidemiology
Epidemiology is the study and analysis of the distribution (who, when, and where), patterns and determinants of health and disease conditions in a defined population. It is a cornerstone of public health, and shapes policy decisions and evidence-based practice by identifying risk factors for disease and targets for preventive healthcare. Epidemiologists help with study design, collection, and statistical analysis of data, amend interpretation and dissemination of results (including peer review and occasional systematic review). Epidemiology has helped develop methodology used in clinical research, public health studies, and, to a lesser extent, basic research in the biological sciences. Major areas of epidemiological study include disease causation, transmission, outbreak investigation, disease surveillance, environmental epidemiology, forensic epidemiology, occupational epidemiology, screening, biomonitoring, and comparisons of treatment effects such as in clinical trials. ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Inverse Probability Weighting
Inverse probability weighting is a statistical technique for calculating statistics standardized to a pseudo-population different from that in which the data was collected. Study designs with a disparate sampling population and population of target inference (target population) are common in application. There may be prohibitive factors barring researchers from directly sampling from the target population such as cost, time, or ethical concerns. A solution to this problem is to use an alternate design strategy, e.g. stratified sampling. Weighting, when correctly applied, can potentially improve the efficiency and reduce the bias of unweighted estimators. One very early weighted estimator is the Horvitz–Thompson estimator of the mean. When the sampling probability is known, from which the sampling population is drawn from the target population, then the inverse of this probability is used to weight the observations. This approach has been generalized to many aspects of statistics un ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Zidovudine
Zidovudine (ZDV), also known as azidothymidine (AZT), is an antiretroviral medication used to prevent and treat HIV/AIDS. It is generally recommended for use in combination with other antiretrovirals. It may be used to prevent mother-to-child spread during birth or after a needlestick injury or other potential exposure. It is sold both by itself and together as lamivudine/zidovudine and abacavir/lamivudine/zidovudine. It can be used by mouth or by slow injection into a vein. Common side effects include headaches, fever, and nausea. Serious side effects include liver problems, muscle damage, and high blood lactate levels. It is commonly used in pregnancy and appears to be safe for the baby. ZDV is of the nucleoside analog reverse-transcriptase inhibitor (NRTI) class. It works by inhibiting the enzyme reverse transcriptase that HIV uses to make DNA and therefore decreases replication of the virus. Zidovudine was first described in 1964. It was approved in the United States i ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
AIDS
Human immunodeficiency virus infection and acquired immunodeficiency syndrome (HIV/AIDS) is a spectrum of conditions caused by infection with the human immunodeficiency virus (HIV), a retrovirus. Following initial infection an individual may not notice any symptoms, or may experience a brief period of influenza-like illness. Typically, this is followed by a prolonged incubation period with no symptoms. If the infection progresses, it interferes more with the immune system, increasing the risk of developing common infections such as tuberculosis, as well as other opportunistic infections, and tumors which are rare in people who have normal immune function. These late symptoms of infection are referred to as acquired immunodeficiency syndrome (AIDS). This stage is often also associated with unintended weight loss. HIV is spread primarily by unprotected sex (including anal and vaginal sex), contaminated blood transfusions, hypodermic needles, and from mother to child duri ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Alanine Aminotransferase
Alanine transaminase (ALT) is a transaminase enzyme (). It is also called alanine aminotransferase (ALT or ALAT) and was formerly called serum glutamate-pyruvate transaminase or serum glutamic-pyruvic transaminase (SGPT) and was first characterized in the mid-1950s by Arthur Karmen and colleagues. ALT is found in plasma and in various body tissues but is most common in the liver. It catalyzes the two parts of the alanine cycle. Serum ALT level, serum AST (aspartate transaminase) level, and their ratio (AST/ALT ratio) are commonly measured clinically as biomarkers for liver health. The tests are part of blood panels. The half-life of ALT in the circulation approximates 47 hours. Aminotransferase is cleared by sinusoidal cells in the liver. Function ALT catalyzes the transfer of an amino group from L-alanine to α-ketoglutarate, the products of this reversible transamination reaction being pyruvate and L-glutamate. : L-alanine + α-ketoglutarate ⇌ pyruvate + L-glutamate ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Bilirubin
Bilirubin (BR) (Latin for "red bile") is a red-orange compound that occurs in the normal catabolic pathway that breaks down heme in vertebrates. This catabolism is a necessary process in the body's clearance of waste products that arise from the destruction of aged or abnormal red blood cells. In the first step of bilirubin synthesis, the heme molecule is stripped from the hemoglobin molecule. Heme then passes through various processes of porphyrin catabolism, which varies according to the region of the body in which the breakdown occurs. For example, the molecules excreted in the urine differ from those in the feces. The production of biliverdin from heme is the first major step in the catabolic pathway, after which the enzyme biliverdin reductase performs the second step, producing bilirubin from biliverdin.Boron W, Boulpaep E. Medical Physiology: a cellular and molecular approach, 2005. 984–986. Elsevier Saunders, United States. Ultimately, bilirubin is broken down within ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
James Robins
James M. Robins is an epidemiologist and biostatistician best known for advancing methods for drawing causal inferences from complex observational studies and randomized trials, particularly those in which the treatment varies with time. He is the 2013 recipient of the Nathan Mantel Award for lifetime achievement in statistics and epidemiology, and a recipient of the 202Rousseeuw Prize in Statistics jointly with Miguel Hernán, Eric Tchetgen-Tchetgen, Andrea Rotnitzky and Thomas Richardson. He graduated in medicine from Washington University in St. Louis in 1976. He is currently Mitchell L. and Robin LaFoley Dong Professor of Epidemiology at Harvard T.H. Chan School of Public Health. He has published over 100 papers in academic journals and is an ISI highly cited researcher. Biography Robins attended Harvard College with the class of 1971, concentrating in mathematics and philosophy. He was elected to Phi Beta Kappa, but did not graduate. He went on to attend Washington Univer ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Babette Brumback
Babette Anne Brumback is an American biostatistician known for her work on causal inference. She is a professor of biostatistics at the University of Florida. Education and career Brumback earned a bachelor's degree in electrical engineering at the University of Virginia in 1988. She went to the University of California, Berkeley for graduate study, originally in electrical engineering and computer science but then switching to statistics; she earned a master's degree in 1992 and completed her Ph.D. in 1996. Her dissertation, ''Statistical Methods for Hormone Data'', was supervised by John A. Rice. After postdoctoral research at Harvard University she became an assistant professor of biostatistics at the University of Washington in 1999, and while there also became affiliated with the Fred Hutchinson Cancer Research Center. She moved to the University of California, Los Angeles in 2002 and again to the University of Florida in 2004. Honors and awards Brumback chaired the Stati ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Miguel Hernán
Miguel Hernán is a Spanish–American epidemiologist. He is the Director of the CAUSALab, Kolokotrones Professor of Biostatistics and Epidemiology at the Harvard T.H. Chan School of Public Health, and Member of the Faculty at the Harvard–MIT Program in Health Sciences and Technology. Hernán conducts research to learn what works to improve human health. Together with his collaborators from several countries, he designs analyses of healthcare databases, epidemiologic studies, and randomized trials. He is a Global Highly Cited Researcher. His free edX course ''Causal Diagrams'' has had over 50,000 registrations. His book ''Causal Inference: What If'', co-authored with James Robins is also freely available online and widely used for the training of researchers. Hernán is Editor Emeritus of Epidemiology (journal) and past Associate Editor of Biometrics (journal), American Journal of Epidemiology, and the Journal of the American Statistical Association. He has been a special Govern ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Statistical Models
A statistical model is a mathematical model that embodies a set of statistical assumptions concerning the generation of sample data (and similar data from a larger population). A statistical model represents, often in considerably idealized form, the data-generating process. A statistical model is usually specified as a mathematical relationship between one or more random variables and other non-random variables. As such, a statistical model is "a formal representation of a theory" ( Herman Adèr quoting Kenneth Bollen). All statistical hypothesis tests and all statistical estimators are derived via statistical models. More generally, statistical models are part of the foundation of statistical inference. Introduction Informally, a statistical model can be thought of as a statistical assumption (or set of statistical assumptions) with a certain property: that the assumption allows us to calculate the probability of any event. As an example, consider a pair of ordinary six- ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
