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  2. Matching (statistics) - Wikipedia

    en.wikipedia.org/wiki/Matching_(statistics)

    Matching is a statistical technique that evaluates the effect of a treatment by comparing the treated and the non-treated units in an observational study or quasi-experiment (i.e. when the treatment is not randomly assigned).

  3. 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 ...

  4. Conditional logistic regression - Wikipedia

    en.wikipedia.org/wiki/Conditional_logistic...

    In fact, it can be shown that the unconditional analysis of matched pair data results in an estimate of the odds ratio which is the square of the correct, conditional one. [2] In addition to tests based on logistic regression, several other tests existed before conditional logistic regression for matched data as shown in related tests. However ...

  5. Record linkage - Wikipedia

    en.wikipedia.org/wiki/Record_linkage

    Record linkage (also known as data matching, data linkage, entity resolution, and many other terms) is the task of finding records in a data set that refer to the same entity across different data sources (e.g., data files, books, websites, and databases).

  6. Exact statistics - Wikipedia

    en.wikipedia.org/wiki/Exact_statistics

    Exact statistics, such as that described in exact test, is a branch of statistics that was developed to provide more accurate results pertaining to statistical testing and interval estimation by eliminating procedures based on asymptotic and approximate statistical methods.

  7. Predictive mean matching - Wikipedia

    en.wikipedia.org/wiki/Predictive_mean_matching

    Predictive mean matching (PMM) [1] is a widely used [2] statistical imputation method for missing values, first proposed by Donald B. Rubin in 1986 [3] and R. J. A. Little in 1988. [ 4 ] It aims to reduce the bias introduced in a dataset through imputation, by drawing real values sampled from the data. [ 5 ]

  8. 68–95–99.7 rule - Wikipedia

    en.wikipedia.org/wiki/68–95–99.7_rule

    In statistics, the 68–95–99.7 rule, also known as the empirical rule, and sometimes abbreviated 3sr, is a shorthand used to remember the percentage of values that lie within an interval estimate in a normal distribution: approximately 68%, 95%, and 99.7% of the values lie within one, two, and three standard deviations of the mean, respectively.

  9. SPSS - Wikipedia

    en.wikipedia.org/wiki/SPSS

    SPSS Statistics is a statistical software suite developed by IBM for data management, advanced analytics, multivariate analysis, business intelligence, and criminal investigation. Long produced by SPSS Inc. , it was acquired by IBM in 2009.