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A forest plot, also known as a blobbogram, is a graphical display of estimated results from a number of scientific studies addressing the same question, along with the overall results. [1] It was developed for use in medical research as a means of graphically representing a meta-analysis of the results of randomized controlled trials .
Line plot survey is a systematic sampling technique used on land surfaces for laying out sample plots within a rectangular grid to conduct forest inventory or agricultural research. It is a specific type of systematic sampling , similar to other statistical sampling methods such as random sampling , but more straightforward to carry out in ...
Additionally, the idea that a forest plot can demonstrate that "no more studies are necessary" is--to my mind--incorrect.Jimjamjak 11:49, 27 January 2020 (UTC) I find examples useful and this example was an iconic part of the spread of meta-analysis. We should certainly seek to fix dead links.
[2] [5] [6] Examples of appropriate visualizations include the scatter plot for regression, and Gardner–Altman plots for two independent groups. [27] While historical data-group plots (bar charts, box plots, and violin plots) do not display the comparison, estimation plots add a second axis to explicitly visualize the effect size. [28]
Funnel plots, introduced by Light and Pillemer in 1984 [1] and discussed in detail by Matthias Egger and colleagues, [2] [3] are useful adjuncts to meta-analyses. A funnel plot is a scatterplot of treatment effect against a measure of study precision.
Scatter plot; Scatterplot smoothing; Scott's rule; Scree plot; Seasonal subseries plot; Self-similarity matrix; Semi-log plot; Sequence logo; Shewhart individuals control chart; Sina plot; Smoothing; Spaghetti plot; Spatial distribution; Stem-and-leaf display; Streamgraph; Sturges's rule
In statistics, a Galbraith plot (also known as Galbraith's radial plot or just radial plot) is one way of displaying several estimates of the same quantity that have different standard errors. [1] Example for Galbraith's radial plot. It can be used to examine heterogeneity in a meta-analysis, as an alternative or supplement to a forest plot.
Plots play an important role in statistics and data analysis. The procedures here can broadly be split into two parts: quantitative and graphical. Quantitative techniques are a set of statistical procedures that yield numeric or tabular output. Examples of quantitative techniques include: [1] hypothesis testing; analysis of variance