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  1. Generalized Linear Models - IBM

    A shipping company can use generalized linear models to fit a Poisson regression to damage counts for several types of ships constructed in different time periods, and the resulting model …

  2. GLM Multivariate Analysis - IBM

    Using this general linear model procedure, you can test null hypotheses about the effects of factor variables on the means of various groupings of a joint distribution of dependent variables.

  3. GLM Univariate Analysis - IBM

    Using this General Linear Model procedure, you can test null hypotheses about the effects of other variables on the means of various groupings of a single dependent variable. You can …

  4. Generalized linear mixed models - IBM

    Medical researchers can use a generalized linear mixed model to determine whether a new anticonvulsant drug can reduce a patient's rate of epileptic seizures. Repeated measurements …

  5. General Linear Model (GLM) and MANOVA (GLM command) - IBM

    Saving of a datafile in IBM® SPSS® Statistics format with parameter estimates and their degrees of freedom and significance level.

  6. GLM Repeated Measures - IBM

    Using this general linear model procedure, you can test null hypotheses about the effects of both the between-subjects factors and the within-subjects factors. You can investigate interactions …

  7. Generalized Linear Models Statistics - IBM

    Model summary statistics. Displays model fit tests, including likelihood-ratio statistics for the model fit omnibus test and statistics for the Type I or III contrasts for each effect.

  8. GLM Post Hoc Comparisons - IBM

    GLM Multivariate and GLM Repeated Measures are available only if you have SPSS® Statistics Standard Edition or the Advanced Statistics Option installed. The Bonferroni and Tukey's …

  9. Obtaining a generalized linear mixed model - IBM

    This feature requires SPSS® Statistics Standard Edition or the Advanced Statistics Option.

  10. IBM Documentation

    Explore IBM's Generalized Linear Models documentation for SPSS Statistics, offering insights into model types, predictors, and response categorizations.