Taylor Series Method
The practical application of a Taylor series expansion to derive an approximate variance formula for a function of random variables.
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The practical application of a Taylor series expansion to derive an approximate variance formula for a function of random variables.
A single numerical value calculated from sample data during a hypothesis test, used to judge whether to reject the null hypothesis.
The degree of agreement between scores from the same instrument given to the same people on two separate occasions, when no real change is expected.
Statistical methods analysing data on the time until a specific event occurs, such as death, while appropriately handling censored observations.
An interval calculated to contain a specified proportion of an entire population's values with a given confidence, unlike a confidence or prediction interval.
A statistical approach identifying and characterising distinct patterns of change in an outcome over time, often revealing subgroups with different courses.
The change in an outcome attributable to a specific treatment, distinguished from changes that would have occurred regardless due to other factors.
A situation in survival or longitudinal analysis where certain observations are systematically excluded based on a variable's value, such as required registration.
An individual patient data meta-analysis first analysing each study separately, then combining the resulting study-level estimates using standard methods.
A hypothesis test assessing evidence for an effect in either direction, without specifying in advance whether it is expected to be better or worse.
In hypothesis testing, the error of incorrectly rejecting a true null hypothesis, concluding a genuine effect exists when it does not.
In hypothesis testing, the error of failing to reject a false null hypothesis, concluding no effect exists when a genuine effect is present.
A property of an estimator whose expected value, across repeated samples, equals the true underlying value of the parameter being estimated.
A probability distribution in which every value within a defined range is equally likely to occur.
A correlation structure for repeated measures allowing the correlation between every pair of time points to be estimated freely and independently.
A dispersion measure representing the average squared deviation of individual data points from the mean of a dataset.
A regression diagnostic quantifying how much an estimated coefficient's variance is inflated by correlation with other predictors, higher values meaning worse multicollinearity.
An orthogonal factor rotation maximising the variance of squared loadings within each factor, tending to make each variable load strongly on only one factor.
The degree to which repeated measurements on the same individual fluctuate over time, unlike between-subject variation reflecting differences across individuals.
In generalised estimating equations, an assumed correlation structure among repeated observations, improving statistical efficiency even if not perfectly correct.