Random effects modelIn statistics, a random effects model, also called a variance components model, is a statistical model where the model parameters are random variables. It is a kind of hierarchical linear model, which assumes that the data being analysed are drawn from a hierarchy of different populations whose differences relate to that hierarchy. A random effects model is a special case of a mixed model.
Big dataBig data primarily refers to data sets that are too large or complex to be dealt with by traditional data-processing application software. Data with many entries (rows) offer greater statistical power, while data with higher complexity (more attributes or columns) may lead to a higher false discovery rate. Though used sometimes loosely partly because of a lack of formal definition, the interpretation that seems to best describe big data is the one associated with a large body of information that we could not comprehend when used only in smaller amounts.
Multilevel modelMultilevel models (also known as hierarchical linear models, linear mixed-effect model, mixed models, nested data models, random coefficient, random-effects models, random parameter models, or split-plot designs) are statistical models of parameters that vary at more than one level. An example could be a model of student performance that contains measures for individual students as well as measures for classrooms within which the students are grouped.
Post-concussion syndromePost-concussion syndrome (PCS), also known as persisting symptoms after concussion, is a set of symptoms that may continue for weeks, months, years after a concussion. PCS is medically classified as a mild traumatic brain injury (TBI). About 35% of people with concussion experience persistent or prolonged symptoms 3 to 6 months after injury. Prolonged concussion is defined as having concussion symptoms for over four weeks following the first accident in youth and for weeks or months in adults.
Chronic traumatic encephalopathyChronic traumatic encephalopathy (CTE) is a neurodegenerative disease linked to repeated trauma to the head. The encephalopathy symptoms can include behavioral problems, mood problems, and problems with thinking. The disease often gets worse over time and can result in dementia. Most documented cases have occurred in athletes involved in striking-based combat sports, such as boxing, kickboxing, mixed martial arts, and Muay Thai—hence its original name dementia pugilistica (Latin for "fistfighter's dementia")—and contact sports such as American football, Australian rules football, professional wrestling, ice hockey, rugby, and association football (soccer), and military combat arms occupations.
Medical diagnosisMedical diagnosis (abbreviated Dx, Dx, or Ds) is the process of determining which disease or condition explains a person's symptoms and signs. It is most often referred to as diagnosis with the medical context being implicit. The information required for diagnosis is typically collected from a history and physical examination of the person seeking medical care. Often, one or more diagnostic procedures, such as medical tests, are also done during the process. Sometimes the posthumous diagnosis is considered a kind of medical diagnosis.
Indication (medicine)In medicine, an indication is a valid reason to use a certain test, medication, procedure, or surgery. There can be multiple indications to use a procedure or medication. An indication can commonly be confused with the term diagnosis. A diagnosis is the assessment that a particular [medical] condition is present while an indication is a reason for use. The opposite of an indication is a contraindication, a reason to withhold a certain medical treatment because the risks of treatment clearly outweigh the benefits.
Differential diagnosisIn healthcare, a differential diagnosis (DDx) is a method of analysis of a patient's history and physical examination to arrive at the correct diagnosis. It involves distinguishing a particular disease or condition from others that present with similar clinical features. Differential diagnostic procedures are used by clinicians to diagnose the specific disease in a patient, or, at least, to consider any imminently life-threatening conditions. Often, each individual option of a possible disease is called a differential diagnosis (e.
Cerebral arteriovenous malformationA cerebral arteriovenous malformation (cerebral AVM, CAVM, cAVM, brain AVM, or BAVM) is an abnormal connection between the arteries and veins in the brain—specifically, an arteriovenous malformation in the cerebrum. The most frequently observed problems related to a cerebral arteriovenous malformation (AVM) are headaches and seizures, cranial nerve afflictions including pinched nerve and palsy, backaches, neckaches, and nausea from coagulated blood that has made its way down to be dissolved in the cerebrospinal fluid.
Data scienceData science is an interdisciplinary academic field that uses statistics, scientific computing, scientific methods, processes, algorithms and systems to extract or extrapolate knowledge and insights from noisy, structured, and unstructured data. Data science also integrates domain knowledge from the underlying application domain (e.g., natural sciences, information technology, and medicine). Data science is multifaceted and can be described as a science, a research paradigm, a research method, a discipline, a workflow, and a profession.
Cohort studyA cohort study is a particular form of longitudinal study that samples a 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-section at intervals through time. It is a type of panel study where the individuals in the panel share a common characteristic.
Data dredgingData dredging (also known as data snooping or p-hacking) is the misuse of data analysis to find patterns in data that can be presented as statistically significant, thus dramatically increasing and understating the risk of false positives. This is done by performing many statistical tests on the data and only reporting those that come back with significant results.
