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Meta-regression
Meta-regression is defined to be a meta-analysis that uses regression analysis to combine, compare, and synthesize research findings from multiple studies while adjusting for the effects of available covariates on a response variable. A meta-regression analysis aims to reconcile conflicting studies or corroborate consistent ones; a meta-regression analysis is therefore characterized by the collated studies and their corresponding data sets—whether the response variable is study-level (or equivalently ''aggregate'') data or individual participant data (or individual patient data in medicine). A data set is ''aggregate'' when it consists of summary statistics such as the sample mean, effect size, or odds ratio. On the other hand, individual participant data are in a sense ''raw'' in that all observations are reported with no abridgment and therefore no information loss. Aggregate data are easily compiled through internet search engines and therefore not expensive. However, individu ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Meta-analysis
A meta-analysis is a statistical analysis that combines the results of multiple scientific studies. Meta-analyses can be performed when there are multiple scientific studies addressing the same question, with each individual study reporting measurements that are expected to have some degree of error. The aim then is to use approaches from statistics to derive a pooled estimate closest to the unknown common truth based on how this error is perceived. Meta-analytic results are considered the most trustworthy source of evidence by the evidence-based medicine literature.Herrera Ortiz AF., Cadavid Camacho E, Cubillos Rojas J, Cadavid Camacho T, Zoe Guevara S, Tatiana Rincón Cuenca N, Vásquez Perdomo A, Del Castillo Herazo V, & Giraldo Malo R. A Practical Guide to Perform a Systematic Literature Review and Meta-analysis. Principles and Practice of Clinical Research. 2022;7(4):47–57. https://doi.org/10.21801/ppcrj.2021.74.6 Not only can meta-analyses provide an estimate of the un ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Variance-stabilizing Transformation
In applied statistics, a variance-stabilizing transformation is a data transformation that is specifically chosen either to simplify considerations in graphical exploratory data analysis or to allow the application of simple regression-based or analysis of variance techniques. Overview The aim behind the choice of a variance-stabilizing transformation is to find a simple function ''ƒ'' to apply to values ''x'' in a data set to create new values such that the variability of the values ''y'' is not related to their mean value. For example, suppose that the values x are realizations from different Poisson distributions: i.e. the distributions each have different mean values ''μ''. Then, because for the Poisson distribution the variance is identical to the mean, the variance varies with the mean. However, if the simple variance-stabilizing transformation :y=\sqrt \, is applied, the sampling variance associated with observation will be nearly constant: see Anscombe transform for d ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Systematic Review
A systematic review is a Literature review, scholarly synthesis of the evidence on a clearly presented topic using critical methods to identify, define and assess research on the topic. A systematic review extracts and interprets data from published studies on the topic, then analyzes, describes, and summarizes interpretations into a refined conclusion. For example, a systematic review of randomized controlled trials is a way of summarizing and implementing evidence-based medicine. While a systematic review may be applied in the Biomedical research, biomedical or health care context, it may also be used where an assessment of a precisely defined subject can advance understanding in a field of research. A systematic review may examine clinical tests, public health interventions, environmental interventions, social interventions, adverse effects, qualitative evidence syntheses, methodological reviews, policy reviews, and economic evaluations. An understanding of systematic review ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Statistical Hypothesis Testing
A statistical hypothesis test is a method of statistical inference used to decide whether the data at hand sufficiently support a particular hypothesis. Hypothesis testing allows us to make probabilistic statements about population parameters. History Early use While hypothesis testing was popularized early in the 20th century, early forms were used in the 1700s. The first use is credited to John Arbuthnot (1710), followed by Pierre-Simon Laplace (1770s), in analyzing the human sex ratio at birth; see . Modern origins and early controversy Modern significance testing is largely the product of Karl Pearson ( ''p''-value, Pearson's chi-squared test), William Sealy Gosset ( Student's t-distribution), and Ronald Fisher ("null hypothesis", analysis of variance, "significance test"), while hypothesis testing was developed by Jerzy Neyman and Egon Pearson (son of Karl). Ronald Fisher began his life in statistics as a Bayesian (Zabell 1992), but Fisher soon grew disenchanted with t ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Multivariate Normal Distribution
In probability theory and statistics, the multivariate normal distribution, multivariate Gaussian distribution, or joint normal distribution is a generalization of the one-dimensional (univariate) normal distribution to higher dimensions. One definition is that a random vector is said to be ''k''-variate normally distributed if every linear combination of its ''k'' components has a univariate normal distribution. Its importance derives mainly from the multivariate central limit theorem. The multivariate normal distribution is often used to describe, at least approximately, any set of (possibly) correlated real-valued random variables each of which clusters around a mean value. Definitions Notation and parameterization The multivariate normal distribution of a ''k''-dimensional random vector \mathbf = (X_1,\ldots,X_k)^ can be written in the following notation: : \mathbf\ \sim\ \mathcal(\boldsymbol\mu,\, \boldsymbol\Sigma), or to make it explicitly known that ''X'' i ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
De Moivre–Laplace Theorem
In probability theory, the de Moivre–Laplace theorem, which is a special case of the central limit theorem, states that the normal distribution may be used as an approximation to the binomial distribution under certain conditions. In particular, the theorem shows that the probability mass function of the random number of "successes" observed in a series of n statistical independence, independent Bernoulli trials, each having probability p of success (a binomial distribution with n trials), Convergence in distribution, converges to the probability density function of the normal distribution with mean np and standard deviation \sqrt, as n grows large, assuming p is not 0 or 1. The theorem appeared in the second edition of ''The Doctrine of Chances'' by Abraham de Moivre, published in 1738. Although de Moivre did not use the term "Bernoulli trials", he wrote about the probability distribution of the number of times "heads" appears when a coin is tossed 3600 times. This is one ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Fisher Transformation
In statistics, the Fisher transformation (or Fisher ''z''-transformation) of a Pearson correlation coefficient is its inverse hyperbolic tangent (artanh). When the sample correlation coefficient ''r'' is near 1 or -1, its distribution is highly Skewness, skewed, which makes it difficult to estimate confidence intervals and apply tests of significance for the population correlation coefficient ρ. The Fisher transformation solves this problem by yielding a variable whose distribution is approximately normally distributed, with a variance that is stable over different values of ''r''. Definition Given a set of ''N'' bivariate sample pairs (''X''''i'', ''Y''''i''), ''i'' = 1, …, ''N'', the Pearson product-moment correlation coefficient, sample correlation coefficient ''r'' is given by :r = \frac = \frac. Here \operatorname(X,Y) stands for the covariance between the variables X and Y and \sigma stands for the standard deviation of the respective var ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Logit
In statistics, the logit ( ) function is the quantile function associated with the standard logistic distribution. It has many uses in data analysis and machine learning, especially in data transformations. Mathematically, the logit is the inverse of the standard logistic function \sigma(x) = 1/(1+e^), so the logit is defined as :\operatorname p = \sigma^(p) = \ln \frac \quad \text \quad p \in (0,1). Because of this, the logit is also called the log-odds since it is equal to the logarithm of the odds \frac where is a probability. Thus, the logit is a type of function that maps probability values from (0, 1) to real numbers in (-\infty, +\infty), akin to the probit function. Definition If is a probability, then is the corresponding odds; the of the probability is the logarithm of the odds, i.e.: :\operatorname(p)=\ln\left( \frac \right) =\ln(p)-\ln(1-p)=-\ln\left( \frac-1\right)=2\operatorname(2p-1) The base of the logarithm function used is of little importance in t ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Regression Analysis
In statistical modeling, regression analysis is a set of statistical processes for estimating the relationships between a dependent variable (often called the 'outcome' or 'response' variable, or a 'label' in machine learning parlance) and one or more independent variables (often called 'predictors', 'covariates', 'explanatory variables' or 'features'). The most common form of regression analysis is linear regression, in which one finds the line (or a more complex linear combination) that most closely fits the data according to a specific mathematical criterion. For example, the method of ordinary least squares computes the unique line (or hyperplane) that minimizes the sum of squared differences between the true data and that line (or hyperplane). For specific mathematical reasons (see linear regression), this allows the researcher to estimate the conditional expectation (or population average value) of the dependent variable when the independent variables take on a given ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Hierarchy Of Evidence
A hierarchy of evidence (or levels of evidence) is a heuristic used to rank the relative strength of results obtained from scientific research. There is broad agreement on the relative strength of large-scale, epidemiological studies. More than 80 different hierarchies have been proposed for assessing medical evidence. The design of the study (such as a case report for an individual patient or a blinded randomized controlled trial) and the endpoints measured (such as survival or quality of life) affect the strength of the evidence. In clinical research, the best evidence for treatment efficacy is mainly from meta-analyses of randomized controlled trials (RCTs). Systematic reviews of completed, high-quality randomized controlled trials – such as those published by the Cochrane Collaboration – rank the same as systematic review of completed high-quality observational studies in regard to the study of side effects. Evidence hierarchies are often applied in evidence-based practic ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Therapy
A therapy or medical treatment (often abbreviated tx, Tx, or Tx) is the attempted remediation of a health problem, usually following a medical diagnosis. As a rule, each therapy has indications and contraindications. There are many different types of therapy. Not all therapies are effective. Many therapies can produce unwanted adverse effects. ''Medical treatment'' and ''therapy'' are generally considered synonyms. However, in the context of mental health, the term ''therapy'' may refer specifically to psychotherapy. History Before the creating of therapy as a formal procedure, people told stories to one another to inform and assist about the world. The term "healing through words" was used over 3,500 years ago in Greek and Egyptian writing. The term psychotherapy was invented in the 19th century, and psychoanalysis was founded by Sigmund Freud under a decade later. Semantic field The words ''care'', ''therapy'', ''treatment'', and ''intervention'' overlap in a s ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
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