### SAS Procedures for Latent Class Analysis & Latent

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29-10-2019 · When designing a study to develop a new prediction model with binary or time‐to‐event outcomes, researchers should ensure their sample size is adequate in terms of the number of participants (n) and outcome events (E) relative to the number of predictor parameters (p) considered for inclusion.We propose that the minimum values of n and E (and subsequently the minimum number of … ...read more

### ANOVA (Analysis of variance) | Statistical Software for Excel

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The results given are a residuals analysis, parameters of the models, the model equation, the standardized coefficients, Type I SS, Type III SS, and predictions are displayed. In addition several multiple comparison methods can optionally be performed: Bonferroni's and Dunn-Sidak corrected t test, Tukey's HSD test, Fisher's LSD test, Duncan's test, Newman-Keuls' (SNK) method and the REGWQ … ...read more

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### Generalized Linear Models in R, Part 1: Calculating

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When invoked with the command-line: frama-c -eva -eva-precision 1 first.c. Frama-C creates an analysis project for the file first.c. The -eva option on the command-line causes the Eva plug-in to run and have its results ready before the interface appears.. The -eva-precision option is one of several options that influence the precision of the Eva plug-in. ...read more

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PROC LCA for Latent Class Analysis. In its simplest form, PROC LCA allows the user to fit a latent class model by specifying a SAS data set, the number of latent classes, the items measuring the latent variable, and the number of response categories for each item. ...read more

### Binary Viewer - Download

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### Frama-C - Framework for Modular Analysis of C programs

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