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  2. Pooled analysis - Wikipedia

    en.wikipedia.org/wiki/Pooled_analysis

    A pooled analysis is a statistical technique for combining the results of multiple epidemiological studies. It is one of three types of literature reviews frequently used in epidemiology, along with meta-analysis and traditional narrative reviews. Pooled analyses may be either retrospective or prospective. [1]

  3. Pooled variance - Wikipedia

    en.wikipedia.org/wiki/Pooled_variance

    Pooled variance is an estimate when there is a correlation between pooled data sets or the average of the data sets is not identical. Pooled variation is less precise the more non-zero the correlation or distant the averages between data sets. The variation of data for non-overlapping data sets is:

  4. Blinder–Oaxaca decomposition - Wikipedia

    en.wikipedia.org/wiki/Blinder–Oaxaca_decomposition

    Using Blinder–Oaxaca decomposition one can distinguish between "change of mean" contribution (purple) and "change of effect" contribution. The Blinder–Oaxaca decomposition (/ ˈ b l aɪ n d ər w ɑː ˈ h ɑː k ɑː /) or Kitagawa decomposition, is a statistical method that explains the difference in the means of a dependent variable between two groups by decomposing the gap into within ...

  5. pandas (software) - Wikipedia

    en.wikipedia.org/wiki/Pandas_(software)

    Pandas (styled as pandas) is a software library written for the Python programming language for data manipulation and analysis.In particular, it offers data structures and operations for manipulating numerical tables and time series.

  6. Functional principal component analysis - Wikipedia

    en.wikipedia.org/wiki/Functional_principal...

    Functional principal component analysis (FPCA) is a statistical method for investigating the dominant modes of variation of functional data. Using this method, a random function is represented in the eigenbasis, which is an orthonormal basis of the Hilbert space L 2 that consists of the eigenfunctions of the autocovariance operator .

  7. Multilevel model - Wikipedia

    en.wikipedia.org/wiki/Multilevel_model

    Multilevel models are particularly appropriate for research designs where data for participants are organized at more than one level (i.e., nested data). [2] The units of analysis are usually individuals (at a lower level) who are nested within contextual/aggregate units (at a higher level). [ 3 ]

  8. Data analysis - Wikipedia

    en.wikipedia.org/wiki/Data_analysis

    Data mining is a particular data analysis technique that focuses on statistical modeling and knowledge discovery for predictive rather than purely descriptive purposes, while business intelligence covers data analysis that relies heavily on aggregation, focusing mainly on business information. [4]

  9. Panel data - Wikipedia

    en.wikipedia.org/wiki/Panel_data

    Panel data is a subset of longitudinal data where observations are for the same subjects each time. Time series and cross-sectional data can be thought of as special cases of panel data that are in one dimension only (one panel member or individual for the former, one time point for the latter). A literature search often involves time series ...