### Minimum sample size for developing a multivariable

Standard methods of performing factor analysis ( i.e., those based on a matrix of Pearson’s correlations) assume that the variables are continuous and follow a multivariate normal distribution. If the model includes variables that are dichotomous or ordinal a factor analysis can be performed using a polychoric correlation matrix. ...read more

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### SAS Procedures for Latent Class Analysis & Latent

Since other SO answers link to this question it's worth noting that there is another option now in PyOxidizer.. It's a rust utility which works in some of the same ways as pyinstaller, however has some additional features detailed here, to summarize the key ones:. Single binary of all packages by default with the ability to do a zero-copy load of modules into memory, vs pyinstaller extracting ...read more

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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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30-04-2020 · "There are 10 types of people in this world: those who understand binary and those who don't." [OS_EMBEDDED_MENU_RIGHT:]We work with binaries daily, yet we understand so little about them. By binaries, I mean the executable files that you run daily, right from your command line tools to full-fledged applications. Linux provides a rich set of tools that makes analyzing binaries a breeze ...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

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

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### How can I perform a factor analysis with categorical (or

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Ordinary Least Squares regression provides linear models of continuous variables. However, much data of interest to statisticians and researchers are not continuous and so other methods must be used to create useful predictive models. The glm() command is designed to perform generalized linear models (regressions) on binary outcome data, count data, probability data, proportion data and many ...read more

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### CUDA Binary Utilities :: CUDA Toolkit Documentation

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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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

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