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  2. Missing data - Wikipedia

    en.wikipedia.org/wiki/Missing_data

    There is a beginner guide that provides a step-by-step instruction how to impute data. [17] The expectation-maximization algorithm is an approach in which values of the statistics which would be computed if a complete dataset were available are estimated (imputed), taking into account the pattern of missing data. In this approach, values for ...

  3. Holm–Bonferroni method - Wikipedia

    en.wikipedia.org/wiki/Holm–Bonferroni_method

    The method is as follows: Suppose you have p-values, sorted into order lowest-to-highest , …,, and their corresponding hypotheses , …, (null hypotheses). You want the FWER to be no higher than a certain pre-specified significance level.

  4. Python (programming language) - Wikipedia

    en.wikipedia.org/wiki/Python_(programming_language)

    Python has array index and array slicing expressions in lists, denoted as a[key], a [start: stop] or a [start: stop: step]. Indexes are zero-based, and negative indexes are relative to the end. Slices take elements from the start index up to, but not including, the stop index.

  5. Propensity score matching - Wikipedia

    en.wikipedia.org/wiki/Propensity_score_matching

    SPSS: A dialog box for Propensity Score Matching is available from the IBM SPSS Statistics menu (Data/Propensity Score Matching), and allows the user to set the match tolerance, randomize case order when drawing samples, prioritize exact matches, sample with or without replacement, set a random seed, and maximize performance by increasing ...

  6. Omnibus test - Wikipedia

    en.wikipedia.org/wiki/Omnibus_test

    The "step" line relates to Chi-Square test on the step level while variables included in the model step by step. Note that in the output a step chi-square, is the same as the block chi-square since they both are testing the same hypothesis that the tested variables enter on this step are non-zero.

  7. Error correction model - Wikipedia

    en.wikipedia.org/wiki/Error_correction_model

    The first step of this method is to pretest the individual time series one uses in order to confirm that they are non-stationary in the first place. This can be done by standard unit root DF testing and ADF test (to resolve the problem of serially correlated errors).

  8. SPSS - Wikipedia

    en.wikipedia.org/wiki/SPSS

    In addition, the Python extension allows SPSS to run any of the statistics in the free software package R. From version 14 onwards, SPSS can be driven externally by a Python or a VB.NET program using supplied "plug-ins". (From version 20 onwards, these two scripting facilities, as well as many scripts, are included on the installation media and ...

  9. SPSS Modeler - Wikipedia

    en.wikipedia.org/wiki/SPSS_Modeler

    IBM SPSS Modeler is a data mining and text analytics software application from IBM. It is used to build predictive models and conduct other analytic tasks. It has a visual interface which allows users to leverage statistical and data mining algorithms without programming.