analyze {simsem} | R Documentation |
Data analysis using the model specification
Description
Data analysis using the model specification (linkS4class{SimSem}
) or the mx model object (MxModel
). Data will be multiply imputed if the miss
argument is specified.
Usage
analyze(model, data, package="lavaan", miss=NULL, aux=NULL, group = NULL,
mxMixture = FALSE, ...)
Arguments
model |
The simsem model template ( |
data |
The target dataset |
package |
The package used in data analysis. Currently, only |
miss |
The missing object with the specification of auxiliary variable or the specification for the multiple imputation. |
aux |
List of auxiliary variables |
group |
A group variable. This argument is applicable only when the |
mxMixture |
A logical whether to the analysis model is a mixture model. This argument is applicable when |
... |
Additional arguments in the |
Value
The lavaan
object containing the output
Author(s)
Patrick Miller (University of Notre Dame; pmille13@nd.edu), Sunthud Pornprasertmanit (psunthud@gmail.com)
See Also
Note that users can use functions provided by lavaan
package (lavaan
, cfa
, sem
, or growth
) if they wish to analyze data by lavaan directly.
Examples
loading <- matrix(0, 6, 2)
loading[1:3, 1] <- NA
loading[4:6, 2] <- NA
LY <- bind(loading, 0.7)
latent.cor <- matrix(NA, 2, 2)
diag(latent.cor) <- 1
RPS <- binds(latent.cor, 0.5)
RTE <- binds(diag(6))
VY <- bind(rep(NA,6),2)
CFA.Model <- model(LY = LY, RPS = RPS, RTE = RTE, modelType = "CFA")
dat <- generate(CFA.Model,200)
out <- analyze(CFA.Model,dat)