A tag is a keyword or label that categorizes your question with other, similar questions. Using the right tags makes it easier for others to find and answer your question.
Questions connected to R packages lme4 and nlme for linear, generalized linear and nonlinear mixed effects models. For general questions about mixed models use [mixed-model] tag.
Support Vector Machine refers to "a set of related supervised learning methods that analyze data and recognize patterns, used for classification and regression analysis."
Refers to the AutoRegressive Integrated Moving Average model used in time series modeling both for data description and for forecasting. This model generalizes the ARMA model by including a term for d…
a formalization of relationships between variables in the form of mathematical equations. A statistical model describes how one or more random variables are related to one or mo…
Repeated measures data occur when more than one measurement is collected on the same unit (e.g. subject). Use this tag for RM-ANOVA together with [anova] tag.
Questions seeking external references (books, papers, etc.) about a particular subject. Always use a more specific tag in addition.
more than one response or dependent variable of interest. This can be contrasted with "multiple" or "multivariable" analysis, which typically implies more than one predictor or…
In frequentist hypothesis testing, the $p$-value is the probability of a result as extreme (or more) than the observed result, under the assumption that the null hypothesis is true.
Survival analysis models time to event data, typically time to death or failure time. Censored data are a common problem for survival analyses.
Methods and principles of selecting a subset of attributes for use in further modelling
Refers to a general estimation technique that selects the parameter value to minimize the squared difference between two quantities, such as the observed value of a variable, and the expected value of…
Mathematical re-expression, often nonlinear, of data values. Data are often transformed either to meet the assumptions of a statistical model or to make the results of an analysis more interpretable.
a machine-learning method based on combining the outputs of many decision trees.
IBM SPSS Statistics (formerly SPSS, i.e. "Statistical Package for the Social Sciences") is a proprietary cross-platform general-purpose statistical software package. [For SPSS Modeler, use 'spss-model…
The binomial distribution gives the frequencies of "successes" in a fixed number of independent "trials". Use this tag for questions about data that might be binomially distributed or for questions a…
a field of statistics dealing with applications to economics.
A situation where the effect of an explanatory variable may depend on the value of another explanatory variable.
The expected value of a random variable; or a location measure for a sample.
Drawing conclusions about population parameters from sample data. See https://en.wikipedia.org/wiki/Inference and https://en.wikipedia.org/wiki/Statistical_inference
Refers to any model where a random variable is related to one or more random variables by a function that is linear in a finite number of parameters.
a value that is subject to chance variation (i.e., randomness in a mathematical sense).
Panel data refers to multi-dimensional data frequently involving measurements over time in econometrics. It is also called longitudinal data in biostatistics.
Refers generally to making substantive conclusions from the results of a statistical analysis.
The probability that an event A will occur, when another event B is known to occur or to have occurred. It is commonly denoted by P(A|B).
Prediction of unknown random quantities, using a statistical model.
the square root of the variance of a random variable, an estimator thereof, or a similar measure of the spread of a batch of data.
off-topic on this site. Use this tag for questions concerning creating, processing, or maintaining datasets.
a problem of judging which model from some set performs best. Popular methods include $R^2$, AIC and BIC criteria, test sets, and cross-validation. To some extent, feature selection…
Procedures that rely on relatively few assumptions about underlying probability distributions.
A discrete distribution defined on the non-negative integers that has the property that the mean is equal to the variance.
a resampling method to estimate the sampling distribution of a statistic.
The parameters of a regression model. Most commonly, the values by which the independent variables will be multiplied to get the predicted value of the dependent variable.
a weighted average of all possible values a random variable can take on, with the weights equal to the probability of taking on that value.
very ambiguous. Use it when the question is about sample size and NONE of the following are more appropriate: [small-sample], [large-data], [power-analysis], [power], [underdetermined] or …