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Medical Statistics
Medical statistics deals with applications of statistics to medicine and the health sciences, including epidemiology, public health, forensic medicine, and clinical research. Medical statistics has been a recognized branch of statistics in the United Kingdom for more than 40 years but the term has not come into general use in North America, where the wider term 'biostatistics' is more commonly used.Dodge, Y. (2003) ''The Oxford Dictionary of Statistical Terms'', OUP. However, "biostatistics" more commonly connotes all applications of statistics to biology. Medical statistics is a subdiscipline of statistics. "It is the science of summarizing, collecting, presenting and interpreting data in medical practice, and using them to estimate the magnitude of associations and test hypotheses. It has a central role in medical investigations. It not only provides a way of organizing information on a wider and more formal basis than relying on the exchange of anecdotes and personal experienc ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Statistics
Statistics (from German: '' Statistik'', "description of a 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 surveys and experiments.Dodge, Y. (2006) ''The Oxford Dictionary of Statistical Terms'', Oxford University Press. When census data cannot be collected, statisticians collect data by developing specific experiment designs and survey samples. Representative sampling assures that inferences and conclusions can reasonably extend from the sample to the population as a whole. An ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
BCA Master Of Biostatistics
The BCA (Biostatistics Collaboration of Australia)is a collaboration of six Australian universities offering a national (and international) program of postgraduate courses in Biostatistics. The universities are * The University of Adelaide * Macquarie University * Monash University * The University of Queensland * The University of Sydney * The University of Melbourne The University of Melbourne is a public research university located in Melbourne, Australia. Founded in 1853, it is Australia's second oldest university and the oldest in Victoria. Its main campus is located in Parkville, an inner suburb no ... is an Affiliated Member, where the program is full time on campus and some BCA Units are included. Courses are taught online. Students enrol at their chosen participating university and each unit of study is delivered by a member university. The BCA Graduate Diploma and Masters Programs are accredited by the Statistical Society of Australia. NSW Ministry of Health a ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Force Of Infection
In epidemiology, force of infection (denoted \lambda) is the rate at which susceptible individuals acquire an infectious disease. Because it takes account of susceptibility it can be used to compare the rate of transmission between different groups of the population for the same infectious disease, or even between different infectious diseases. That is to say, \lambda is directly proportional to \beta; the effective transmission rate. : \lambda = \frac Such a calculation is difficult because not all new infections are reported, and it is often difficult to know how many susceptibles were exposed. However, \lambda can be calculated for an infectious disease in an endemic state if homogeneous mixing of the population and a rectangular population distribution (such as that generally found in developed countries), rather than a pyramid, is assumed. In this case, \lambda is given by: : \lambda = \frac where A is the average age of infection. In other words, A is the avera ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Transmission Risks And Rates
Transmission of an infection requires three conditions: *an infectious individual *a susceptible individual *an effective contact between them An effective contact is defined as any kind of contact between two individuals such that, if one individual is infectious and the other susceptible, then the first individual infects the second. Whether or not a particular kind of contact will be effective depends on the infectious agent and its route of transmission. The effective contact rate (denoted ''β'') in a given population for a given infectious disease is measured in effective contacts per unit time. This may be expressed as the total contact rate (the total number of contacts, effective or not, per unit time, denoted \gamma), multiplied by the risk of infection, given contact between an infectious and a susceptible individual. This risk is called the transmission risk and is denoted ''p''. Thus: : \beta = \gamma \times p \, The total contact rate, \gamma, will generally be g ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Prevalence
In epidemiology, prevalence is the proportion of a particular population found to be affected by a medical condition (typically a disease or a risk factor such as smoking or seatbelt use) at a specific time. It is derived by comparing the number of people found to have the condition with the total number of people studied and is usually expressed as a fraction, a percentage, or the number of cases per 10,000 or 100,000 people. Prevalence is most often used in questionnaire studies. Difference between prevalence and incidence Prevalence is the number of disease cases ''present ''in a particular population at a given time, whereas incidence is the number of new cases that ''develop '' during a specified time period. Prevalence answers "How many people have this disease right now?" or "How many people have had this disease during this time period?". Incidence answers "How many people acquired the disease uring a specified time period". However, mathematically, prevalence is propor ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Positive And Negative Predictive Values
The positive and negative predictive values (PPV and NPV respectively) are the proportions of positive and negative results in statistics and diagnostic tests that are true positive and true negative results, respectively. The PPV and NPV describe the performance of a diagnostic test or other statistical measure. A high result can be interpreted as indicating the accuracy of such a statistic. The PPV and NPV are not intrinsic to the test (as true positive rate and true negative rate are); they depend also on the prevalence. Both PPV and NPV can be derived using Bayes' theorem. Although sometimes used synonymously, a ''positive predictive value'' generally refers to what is established by control groups, while a post-test probability refers to a probability for an individual. Still, if the individual's pre-test probability of the target condition is the same as the prevalence in the control group used to establish the positive predictive value, the two are numerically equal. ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Accuracy And Precision
Accuracy and precision are two measures of ''observational error''. ''Accuracy'' is how close a given set of measurements ( observations or readings) are to their '' true value'', while ''precision'' is how close the measurements are to each other. In other words, ''precision'' is a description of '' random errors'', a measure of statistical variability. ''Accuracy'' has two definitions: # More commonly, it is a description of only ''systematic errors'', a measure of statistical bias of a given measure of central tendency; low accuracy causes a difference between a result and a true value; ISO calls this ''trueness''. # Alternatively, ISO defines accuracy as describing a combination of both types of observational error (random and systematic), so high accuracy requires both high precision and high trueness. In the first, more common definition of "accuracy" above, the concept is independent of "precision", so a particular set of data can be said to be accurate, precise, both, ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Null Hypothesis
In scientific research, the null hypothesis (often denoted ''H''0) is the claim that no difference or relationship exists between two sets of data or variables being analyzed. The null hypothesis is that any experimentally observed difference is due to chance alone, and an underlying causative relationship does not exist, hence the term "null". In addition to the null hypothesis, an alternative hypothesis is also developed, which claims that a relationship does exist between two variables. Basic definitions The ''null hypothesis'' and the ''alternative hypothesis'' are types of conjectures used in statistical tests, which are formal methods of reaching conclusions or making decisions on the basis of data. The hypotheses are conjectures about a statistical model of the population, which are based on a sample of the population. The tests are core elements of statistical inference, heavily used in the interpretation of scientific experimental data, to separate scientific claims ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Type I And Type II Errors
In statistical hypothesis testing, a type I error is the mistaken rejection of an actually true null hypothesis (also known as a "false positive" finding or conclusion; example: "an innocent person is convicted"), while a type II error is the failure to reject a null hypothesis that is actually false (also known as a "false negative" finding or conclusion; example: "a guilty person is not convicted"). Much of statistical theory revolves around the minimization of one or both of these errors, though the complete elimination of either is a statistical impossibility if the outcome is not determined by a known, observable causal process. By selecting a low threshold (cut-off) value and modifying the alpha (α) level, the quality of the hypothesis test can be increased. The knowledge of type I errors and type II errors is widely used in medical science, biometrics and computer science. Intuitively, type I errors can be thought of as errors of ''commission'', i.e. the researcher unluc ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
False Positives And False Negatives
A false positive is an error in binary classification in which a test result incorrectly indicates the presence of a condition (such as a disease when the disease is not present), while a false negative is the opposite error, where the test result incorrectly indicates the absence of a condition when it is actually present. These are the two kinds of errors in a binary test, in contrast to the two kinds of correct result (a and a ). They are also known in medicine as a false positive (or false negative) diagnosis, and in statistical classification as a false positive (or false negative) error. In statistical hypothesis testing the analogous concepts are known as type I and type II errors, where a positive result corresponds to rejecting the null hypothesis, and a negative result corresponds to not rejecting the null hypothesis. The terms are often used interchangeably, but there are differences in detail and interpretation due to the differences between medical testing and stat ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Pregnancy Test
A pregnancy test is used to determine whether a female is pregnant or not. The two primary methods are testing for the female pregnancy hormone (human chorionic gonadotropin (hCG)) in blood or urine using a pregnancy test kit, and scanning with ultrasonography. Testing blood for hCG results in the earliest detection of pregnancy. Almost all pregnant women will have a positive urine pregnancy test one week after the first day of a missed menstrual period. Types Human chorionic gonadotropin (hCG) Identified in the early 20th century, human chorionic gonadotropin (hCG) is a glycoprotein hormone that rises quickly in the first few weeks of pregnancy, typically reaching a peak at 8- to 10-weeks gestational age. hCG is produced by what will become the placenta. hCG testing can be performed with a blood (serum) sample (typically done in a medical facility) or with urine (which can be performed in a medical facility or at home). The assays used to detect the presence of hCG in b ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Medical Test
A medical test is a medical procedure performed to detect, diagnose, or monitor diseases, disease processes, susceptibility, or to determine a course of treatment. Medical tests such as, physical and visual exams, diagnostic imaging, genetic testing, chemical and cellular analysis, relating to clinical chemistry and molecular diagnostics, are typically performed in a medical setting. Types of tests By purpose Medical tests can be classified by their purposes, the most common of which are diagnosis, screening and evaluation. Diagnostic A diagnostic test is a procedure performed to confirm or determine the presence of disease in an individual suspected of having a disease, usually following the report of symptoms, or based on other medical test results. This includes posthumous diagnosis. Examples of such tests are: * Using nuclear medicine to examine a patient suspected of having a lymphoma. * Measuring the blood sugar in a person suspected of having diabetes mellitu ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
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