binary variablesIn attempting to represent a multivariable system by a simpler one with only binary variables it is not always possible to achieve the required correlations. This paper explores the extra constr
The algorithms were clearly superior to known techniques dealing with correlations between binary variables to show the toxin producing microorganism. We used experimental toxin isolation from phytoplankton as an example of practical success using the most efficient of the algorithms tested....
to one based on a conditional linear family (CLF) of distributions [Qaqish BF. A family of multivariate binary distributions for simulating correlated binary variables with specified marginal means and correlations. Biometrika. 2003;90:455463] with respect to range restrictions induced on correlations...
Star graphs induce tetrad correlations: for Gaussian as well as for binary variables. Electr. J. Statist. 8, 253-273.Wermuth, N. & Marchetti, G.M (2014). Star graphs induce tetrad correlations: for Gaussian as well as for binary variables. Electronic Jornal of Statistics 8, 253-273....
Computes an tetrachoric correlation matrix for binary variables given the specified correlation matrixn.BB
To avoid this trivial solution, we constrain the interface variables and focus on the simplest case of binary variables. We show that the functional organization of networks with latent binary interface variables can be inferred from the statistical moments of observable network components alone, and ...
Phi Coefficient measures the association between two binary variables, such as living/dead, black/white, or success/failure. It is also known as the Yule phi or Mean Square Contingency Coefficient. This statistical measure is used for contingency tables when at least one variable is nominal and ...
The Xik are binary variables that form a one hot encoding of the integer-valued lag variables Xi from "Lag Penalized Weighted Correlation" section. Xik = 1 if Xi = k, and Xik = 0 if Xi = k . The Xik,j,l are binary variables that are equal to 1 if and only if the lag of...
I ran biserial correlations between continuous and binary variables in SPSS on a large dataset of 762 patients. I correlated 138 regional brain volumes with 7 binary cognitive outcomes to explore the association between regional brain tissue volumes and cognitive impairment. ...
Will you please tell me if there is another solution here? And will you please explain what can cause the latent variables to correlate higher than one, or in other words, what could be wrong with this model that I need to avoid in testing another model?