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Unlike meta-analyses, pooled analyses can only be conducted if the included studies used the same study design and statistical models, and if their respective populations were homogeneous. If individual-level data from the included studies is available, the result of a pooled analysis can be considered more reliable.
In statistics, pooled variance (also known as combined variance, composite variance, or overall variance, and written ) is a method for estimating variance of several different populations when the mean of each population may be different, but one may assume that the variance of each population is the same.
Variants include pooled cross-sectional data, which deals with the observations on the same subjects in different times. In a rolling cross-section, both the presence of an individual in the sample and the time at which the individual is included in the sample are determined randomly. For example, a political poll may decide to interview 1000 ...
The researchers also pooled together data on nearly 21,000 children from 59 studies that reported average IQ scores. Those data showed that children exposed to higher fluoride levels had lower IQ ...
Panel data analysis has three more-or-less independent approaches: independently pooled panels; random effects models; fixed effects models or first differenced models. The selection between these methods depends upon the objective of the analysis, and the problems concerning the exogeneity of the explanatory variables.
A recent pooled analysis published in the journal C ancer looked at drinking coffee and tea and the risk for head and neck cancer. The data examined over 9,500 cases of head and neck cancer and ...
The grand mean or pooled mean is the average of the means of several subsamples, as long as the subsamples have the same number of data points. [1] For example, consider several lots, each containing several items. The items from each lot are sampled for a measure of some variable and the means of the measurements from each lot are computed ...
The meaningfulness of the study data, or power, is indicated by the weight (size) of the box. More meaningful data, such as those from studies with greater sample sizes and smaller confidence intervals, is indicated by a larger sized box than data from less meaningful studies, and they contribute to the pooled result to a greater degree.