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Linear trend estimation is a statistical technique used to analyze data patterns. Data patterns, or trends, occur when the information gathered "tends" to increase or decrease over time. Linear trend estimation essentially creates a straight line on a graph of data that models the general direction that the data is heading.
Linear regression was the first type of regression analysis to be studied rigorously, and to be used extensively in practical applications. [4] This is because models which depend linearly on their unknown parameters are easier to fit than models which are non-linearly related to their parameters and because the statistical properties of the resulting estimators are easier to determine.
Jonckheere's trend test. In statistics, the Jonckheere trend test [1] (sometimes called the Jonckheere–Terpstra [2] test) is a test for an ordered alternative hypothesis within an independent samples (between-participants) design. It is similar to the Kruskal-Wallis test in that the null hypothesis is that several independent samples are from ...
Regression analysis. Segmented regression, also known as piecewise regression or broken-stick regression, is a method in regression analysis in which the independent variable is partitioned into intervals and a separate line segment is fit to each interval. Segmented regression analysis can also be performed on multivariate data by partitioning ...
Mathematically, multilevel analysis with repeated measures is very similar to the analysis of data in which subjects are clustered in groups. However, one point to note is that time-related predictors must be explicitly entered into the model to evaluate trend analyses and to obtain an overall test of the repeated measure.
The Cochran–Armitage test for trend, [1] [2] named for William Cochran and Peter Armitage, is used in categorical data analysis when the aim is to assess for the presence of an association between a variable with two categories and an ordinal variable with k categories. It modifies the Pearson chi-squared test to incorporate a suspected ...
As defined by Theil (1950), the Theil–Sen estimator of a set of two-dimensional points (xi, yi) is the median m of the slopes (yj − yi)/ (xj − xi) determined by all pairs of sample points. Sen (1968) extended this definition to handle the case in which two data points have the same x coordinate. In Sen's definition, one takes the median ...
In statistics, simple linear regression ( SLR) is a linear regression model with a single explanatory variable. [1] [2] [3] [4] [5] That is, it concerns two ...