| generate_observables {transforEmotion} | R Documentation |
Generate observable emotion scores data from latent variables
Description
Function to generate observable data from 2 latent variables (negative and positive affect). The function takes in the latent variable scores, the number of time steps, the number of observable variables per latent factor, and the measurement error variance. It returns a matrix of observable data. The factor loadings are not the same for all observable variables. They have uniform random noise added to them (between -0.15 and 0.15). The loadings are scaled so that the sum of the loadings for each latent factor is 2, to introduce a ceiling effect and to differentiate the dynamics of specific emotions. This is further empahsized by adding small noise to the measurement error variance for each observed variable (between -0.01 and 0.01).
Usage
generate_observables(X, num_steps, num_obs, error, loadings = 0.8)
Arguments
X |
Matrix or Data frame. The (num_steps X 2) matrix of latent variable scores. |
num_steps |
Numeric integer. Number of time steps. |
num_obs |
Numeric integer. The number of observable variables per latent factor. |
error |
Numeric. Measurement error variance. |
loadings |
Numeric (default = 0.8). The default initial loading of the latent variable on the observable variable. |
Value
A (num_steps X num_obs) Matrix or Data frame containing the observable variables.